This document discusses semantic visualization in design computing. It presents an approach for designing visualization schemes that leverage predefined semantics. The approach is based on a combination of cognitive linguistics models of metaphor and form-semantics-function categorization. It includes metaphor analysis, formalization, and evaluation. Examples are provided of visualizing collaborative design data and virtual worlds to illustrate the approach. The goal is to establish and preserve semantic links between form and function in visualization metaphors.
word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings o...Subhajit Sahu
Below are the important points I note from the 2020 paper by Martin Grohe:
- 1-WL distinguishes almost all graphs, in a probabilistic sense
- Classical WL is two dimensional Weisfeiler-Leman
- DeepWL is an unlimited version of WL graph that runs in polynomial time.
- Knowledge graphs are essentially graphs with vertex/edge attributes
ABSTRACT:
Vector representations of graphs and relational structures, whether handcrafted feature vectors or learned representations, enable us to apply standard data analysis and machine learning techniques to the structures. A wide range of methods for generating such embeddings have been studied in the machine learning and knowledge representation literature. However, vector embeddings have received relatively little attention from a theoretical point of view.
Starting with a survey of embedding techniques that have been used in practice, in this paper we propose two theoretical approaches that we see as central for understanding the foundations of vector embeddings. We draw connections between the various approaches and suggest directions for future research.
SVHsIEVs for Navigation in Virtual Urban Environmentcsandit
Many virtual reality applications, such as training, urban design or gaming are based on a rich
semantic description of the environment. This paper describes a new representation of semantic
virtual worlds. Our model, called SVHsIEVs1
should provide a consistent representation of the
following aspects: the simulated environment, its structure, and the knowledge items using
ontology, interactions and tasks that virtual humans can perform in the environment. Our first
main contribution is to show the influence of semantic virtual objects on the environment. Our
second main contribution is to use these semantic informations to manage he tasks of each
virtual object. We propose to define each task by a set of attributes and relationships, which
determines the links between attributes in tasks, and links between other tasks. The architecture
has been successfully tested in 3D dynamic environments for navigation in virtual urban
environments.
Many virtual reality applications, such as training, urban design or gaming are based on a rich
semantic description of the environment. This paper describes a new representation of semantic
virtual worlds. Our model, called SVHsIEVs1should provide a consistent representation of the
following aspects: the simulated environment, its structure, and the knowledge items using
ontology, interactions and tasks that virtual humans can perform in the environment. Our first
main contribution is to show the influence of semantic virtual objects on the environment. Our
second main contribution is to use these semantic informations to manage he tasks of each
virtual object. We propose to define each task by a set of attributes and relationships, which
determines the links between attributes in tasks, and links between other tasks. The architecture
has been successfully tested in 3D dynamic environments for navigation in virtual urban
environments.
The document introduces the visual mapping sentence (MS) methodology for multifaceted research design and analysis. The MS is a visual representation that classifies research variables into facets. It guides hypothesis generation and systematic data collection/analysis. The MS links components of a research domain to suggest relationships between variables and facets. It maps all relevant variables and provides information about excluded variables. Two examples of MS are included in figures to illustrate their use. The MS methodology is presented as a valuable tool that can help address limitations of other research methods by emphasizing conceptual definition and structure of content areas.
An ontology for semantic modelling of virtual worldijaia
This article presents a new representation of semantic virtual environments. We propose to use the ontology as a tool for implementation. Our model, called SVHsIEVs1 provides a consistent representation of the following aspects: the simulated environment, its structure, and the knowledge items using ontology, interactions and tasks that virtual humans can perform in the environment. In SVHsIEVs, we find two type of ontology: the global ontology and the local ontology for Virtual Human. Our architecture has been successfully tested in 3D dynamic environments.
For non-grid 3D images like point clouds and meshes, and inherently graph-based data.
Inherently graph-based data include for example brain connectivity analysis, scientific article citation networks, (social) network analysis, etc.
Alternative download link:
https://www.dropbox.com/s/2o3cofcd6d6e2qt/geometricGraph_deepLearning.pdf?dl=0
4F C A Conceptual Framework For Understanding Architectural WorksCheryl Brown
This document presents a conceptual framework for understanding architectural works. It expands upon Vitruvius' triad of utilitas, venustas, and firmitas by including architectural thinking manifested as a formative concept and situating a design within its related context. The framework aims to provide a robust understanding of architecture that can be used to structure architectural forms, describe existing works, and serve as a foundation for architectural design and pedagogy. It was developed using a grounded theory method and qualitative descriptions to identify the key concepts that constitute architectural works and their relationships.
This document surveys ontology visualization methods. It begins by defining ontologies as sets of concepts and relationships in a domain that have proven useful for digital libraries, the semantic web, and personalized information management. However, effectively visualizing ontologies is challenging due to the complex relationships and attributes involved. The document aims to categorize existing ontology visualization techniques and their characteristics in order to help with method selection and further research. It provides context on related work reviewing data visualization techniques before analyzing ontology visualization methods in detail.
word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings o...Subhajit Sahu
Below are the important points I note from the 2020 paper by Martin Grohe:
- 1-WL distinguishes almost all graphs, in a probabilistic sense
- Classical WL is two dimensional Weisfeiler-Leman
- DeepWL is an unlimited version of WL graph that runs in polynomial time.
- Knowledge graphs are essentially graphs with vertex/edge attributes
ABSTRACT:
Vector representations of graphs and relational structures, whether handcrafted feature vectors or learned representations, enable us to apply standard data analysis and machine learning techniques to the structures. A wide range of methods for generating such embeddings have been studied in the machine learning and knowledge representation literature. However, vector embeddings have received relatively little attention from a theoretical point of view.
Starting with a survey of embedding techniques that have been used in practice, in this paper we propose two theoretical approaches that we see as central for understanding the foundations of vector embeddings. We draw connections between the various approaches and suggest directions for future research.
SVHsIEVs for Navigation in Virtual Urban Environmentcsandit
Many virtual reality applications, such as training, urban design or gaming are based on a rich
semantic description of the environment. This paper describes a new representation of semantic
virtual worlds. Our model, called SVHsIEVs1
should provide a consistent representation of the
following aspects: the simulated environment, its structure, and the knowledge items using
ontology, interactions and tasks that virtual humans can perform in the environment. Our first
main contribution is to show the influence of semantic virtual objects on the environment. Our
second main contribution is to use these semantic informations to manage he tasks of each
virtual object. We propose to define each task by a set of attributes and relationships, which
determines the links between attributes in tasks, and links between other tasks. The architecture
has been successfully tested in 3D dynamic environments for navigation in virtual urban
environments.
Many virtual reality applications, such as training, urban design or gaming are based on a rich
semantic description of the environment. This paper describes a new representation of semantic
virtual worlds. Our model, called SVHsIEVs1should provide a consistent representation of the
following aspects: the simulated environment, its structure, and the knowledge items using
ontology, interactions and tasks that virtual humans can perform in the environment. Our first
main contribution is to show the influence of semantic virtual objects on the environment. Our
second main contribution is to use these semantic informations to manage he tasks of each
virtual object. We propose to define each task by a set of attributes and relationships, which
determines the links between attributes in tasks, and links between other tasks. The architecture
has been successfully tested in 3D dynamic environments for navigation in virtual urban
environments.
The document introduces the visual mapping sentence (MS) methodology for multifaceted research design and analysis. The MS is a visual representation that classifies research variables into facets. It guides hypothesis generation and systematic data collection/analysis. The MS links components of a research domain to suggest relationships between variables and facets. It maps all relevant variables and provides information about excluded variables. Two examples of MS are included in figures to illustrate their use. The MS methodology is presented as a valuable tool that can help address limitations of other research methods by emphasizing conceptual definition and structure of content areas.
An ontology for semantic modelling of virtual worldijaia
This article presents a new representation of semantic virtual environments. We propose to use the ontology as a tool for implementation. Our model, called SVHsIEVs1 provides a consistent representation of the following aspects: the simulated environment, its structure, and the knowledge items using ontology, interactions and tasks that virtual humans can perform in the environment. In SVHsIEVs, we find two type of ontology: the global ontology and the local ontology for Virtual Human. Our architecture has been successfully tested in 3D dynamic environments.
For non-grid 3D images like point clouds and meshes, and inherently graph-based data.
Inherently graph-based data include for example brain connectivity analysis, scientific article citation networks, (social) network analysis, etc.
Alternative download link:
https://www.dropbox.com/s/2o3cofcd6d6e2qt/geometricGraph_deepLearning.pdf?dl=0
4F C A Conceptual Framework For Understanding Architectural WorksCheryl Brown
This document presents a conceptual framework for understanding architectural works. It expands upon Vitruvius' triad of utilitas, venustas, and firmitas by including architectural thinking manifested as a formative concept and situating a design within its related context. The framework aims to provide a robust understanding of architecture that can be used to structure architectural forms, describe existing works, and serve as a foundation for architectural design and pedagogy. It was developed using a grounded theory method and qualitative descriptions to identify the key concepts that constitute architectural works and their relationships.
This document surveys ontology visualization methods. It begins by defining ontologies as sets of concepts and relationships in a domain that have proven useful for digital libraries, the semantic web, and personalized information management. However, effectively visualizing ontologies is challenging due to the complex relationships and attributes involved. The document aims to categorize existing ontology visualization techniques and their characteristics in order to help with method selection and further research. It provides context on related work reviewing data visualization techniques before analyzing ontology visualization methods in detail.
This document describes a proposed content-based image retrieval system using backpropagation neural networks (BPNN) and k-means clustering. It begins by discussing CBIR techniques and features like color, texture, and shape. It then outlines the proposed system which includes training a BPNN on image features, validating images, and testing by querying and retrieving similar images. Performance is analyzed based on metrics like accuracy, efficiency, and classification rate. Results show the system achieves up to 98% classification accuracy within 5-6 seconds.
This document outlines Serena Pollastri's year 1 research plan. The research aims to map visualization processes that can contribute to designing future scenarios of sustainable, livable cities. The theoretical framework is based on a "metadesign" approach of collaboratively designing design tools to enable systemic change. The research structure involves literature reviews on visualizations, future scenarios, and cities/liveability. Design experiments are planned, including future visioning workshops and a foresight report. The timeline shows literature reviews and design experiments occurring through 2014-2016, culminating in publications and conferences.
Visualizer for concept relations in an automatic meaning extraction systemPatricia Tavares Boralli
This document discusses a visualizer interface that has been developed for an automatic meaning extraction (AME) system. The visualizer allows users to view concepts and their relationships extracted from text documents in a graph format. It maps concepts as nodes and relationships as edges. Users can search for concepts, view related concepts, and trace relationships back to the original text passages. The visualizer was created to help users interact with and understand the outputs of the AME system, which automatically extracts concepts and relations from documents across various domains.
This document discusses semantic networks and their applications in artificial intelligence. It begins with describing how semantic networks originated in psychology for analyzing relationships between concepts, and were later adopted by AI to analyze textual data. Key applications of semantic networks discussed include idea generation, visual text analysis, and conceptual design. The document also provides historical background on semantic networks and how they are used for knowledge representation.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
Speed has become a way of life. We are asymptotically piling data. Speed can be achieved with new design
processes, techniques, and Technology. Innovations AR and VR are just some of the many forms of
technologies that will play a key role in shaping the Architecture and Planning of tomorrow, making it
future-ready and ushering in a new age of innovation. AR and VR in Architecture & Planning were
introduced as assisting tools and has helped generate multiple design options, expanded possibilities of
visualization, and provided us with more enhanced, detailed, and specific experience in real-time; enabling
us to see the resultsof work on hand well before the commencement of the project. These tools are further
developed for city development decisions, helping citizens interact with local authorities, access public
services, and plan their commute. After reviewing multiple research papers, it had been observed that each
one is moving forward with the changes brought by it, without entirely understanding its role. This paper
provides a summary of theappliance of AR & VR in architecture and planning.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
Speed has become a way of life. We are asymptotically piling data. Speed can be achieved with new design
processes, techniques, and Technology. Innovations AR and VR are just some of the many forms of
technologies that will play a key role in shaping the Architecture and Planning of tomorrow, making it
future-ready and ushering in a new age of innovation. AR and VR in Architecture & Planning were
introduced as assisting tools and has helped generate multiple design options, expanded possibilities of
visualization, and provided us with more enhanced, detailed, and specific experience in real-time; enabling
us to see the resultsof work on hand well before the commencement of the project. These tools are further
developed for city development decisions, helping citizens interact with local authorities, access public
services, and plan their commute. After reviewing multiple research papers, it had been observed that each
one is moving forward with the changes brought by it, without entirely understanding its role. This paper
provides a summary of theappliance of AR & VR in architecture and planning.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
Speed has become a way of life. We are asymptotically piling data. Speed can be achieved with new design
processes, techniques, and Technology. Innovations AR and VR are just some of the many forms of
technologies that will play a key role in shaping the Architecture and Planning of tomorrow, making it
future-ready and ushering in a new age of innovation. AR and VR in Architecture & Planning were
introduced as assisting tools and has helped generate multiple design options, expanded possibilities of
visualization, and provided us with more enhanced, detailed, and specific experience in real-time; enabling
us to see the resultsof work on hand well before the commencement of the project. These tools are further
developed for city development decisions, helping citizens interact with local authorities, access public
services, and plan their commute. After reviewing multiple research papers, it had been observed that each
one is moving forward with the changes brought by it, without entirely understanding its role. This paper
provides a summary of theappliance of AR & VR in architecture and planning.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
This document provides an overview of augmented reality (AR) and virtual reality (VR) technologies and their applications in architecture and urban planning. It first discusses how AR and VR have helped generate multiple design options, improve visualization, and provide more detailed virtual experiences of projects before they are built. It then reviews several research papers on the topics of AR/VR in design. Key applications discussed include enabling better collaboration and ideation, analyzing spatial relationships, and allowing public involvement in design decisions. The document also outlines some challenges to wider adoption of these technologies, such as technical limitations of equipment and the need for more specialized tools tailored for the design field.
This document proposes a data model for managing large point cloud data while integrating semantics. It presents a conceptual model composed of three interconnected meta-models to efficiently store and manage point cloud data, and allow the injection of semantics. A prototype is implemented using Python and PostgreSQL to combine semantic and spatial concepts for queries on indoor point cloud data captured with a terrestrial laser scanner.
This document presents a content-based image retrieval semantic model for shaped and unshaped objects. It proposes classifying objects into two categories: shaped objects with a fixed shape like animals and objects, and unshaped objects without a fixed shape like landscapes. For unshaped objects, local regions are classified by frequency of occurrence and semantic concepts are evaluated using color, shape, and regional dissimilarity factors. For shaped objects, semantic concepts are measured using normalized color, edge detection, particle removal, and shape similarity. Several existing content-based image retrieval techniques are also briefly discussed.
The document proposes an attribute-assisted reranking model for web image search. It uses semantic attributes along with visual features to represent images, constructs a hypergraph to model relationships between images, and performs hypergraph ranking to reorder search results. Attributes provide an intermediate-level semantic description that can help reduce the semantic gap between low-level visual features and high-level meanings. The proposed approach extracts both visual and attribute features from initial search results, builds a hypergraph integrating the two types of features, and learns relevance scores to rerank the images.
Enhancing the Design pattern Framework of Robots Object Selection Mechanism -...INFOGAIN PUBLICATION
This document summarizes a research paper about developing a computer program that can take a 2D photograph as input, analyze it to determine the objects and their 3D structure, and output a 3D representation that can be viewed from any angle. The program makes assumptions about the objects, such as they are constructed from transformations of known 3D models and are supported by other visible objects or a ground plane. It develops processes for 2D to 3D construction and 3D to 2D display that can handle most arrangements of objects with planar surfaces.
This document describes a proposed method to improve image classification accuracy and speed using the bag-of-features model with spatial pooling. The proposed method has two phases: a training phase to create an image feature database, and an evaluation phase to classify new images. In the evaluation phase, spatial pooling is applied to input image features before classification with KNN. Variance-based feature selection is also used to reduce features before KNN classification. Experimental results show the proposed method improves classification accuracy up to 5% and reduces classification time by up to 50% compared to the standard bag-of-features model.
An Attribute-Assisted Reranking Model for Web Image Search1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
An Attribute-Assisted Reranking Model for Web Image Search1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
A novel Image Retrieval System using an effective region based shape represen...CSCJournals
With recent improvements in methods for the acquisition and rendering of shapes, the need for retrieval of shapes from large repositories of shapes has gained prominence. A variety of methods have been proposed that enable the efficient querying of shape repositories for a desired shape or image. Many of these methods use a sample shape as a query and attempt to retrieve shapes from the database that have a similar shape. This paper introduces a novel and efficient shape matching approach for the automatic identification of real world objects. The identification process is applied on isolated objects and requires the segmentation of the image into separate objects, followed by the extraction of representative shape signatures and the similarity estimation of pairs of objects considering the information extracted from the segmentation process and shape signature. We compute a 1D shape signature function from a region shape and use it for region shape representation and retrieval through similarity estimation. The proposed region shape feature is much more efficient to compute than other region shape techniques invariant to image transformation.
The document discusses building conceptual models from sensor data by constructing networks that relate the data and looking for invariants within the network. Specifically, it proposes:
1) Building networks that relate sensor signals to each other using similarity measures.
2) Transporting information through the network using linear operators to relate function spaces.
3) Using network regularization and cycle consistency to find concepts that emerge as fixed points within the network.
International Journal of Computational Engineering Research(IJCER)ijceronline
This document summarizes a research paper on reengineering relational databases to object-oriented databases. It discusses developing an integrated environment that maps a relational schema to an object-oriented schema without modifying the existing relational schema. The proposed system architecture has two major components - one for mapping the relational schema to an object-oriented schema, and another for mapping relational data to objects. The schema mapping process is two-phased - the first phase transforms the relational schema, and the second phase extracts object-oriented structures. The system aims to allow existing applications and data in a relational database to be accessible from object-oriented programs.
The presentation of our Journal First (J1ST) paper entitled "Conceptualisation, measurement, and application of semantic transparency in visual notations" on MODELS 2021: ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems (MODELS)
Formal Models for Context Aware ComputingEditor IJCATR
Context-aware computing refers to a general class of mobile systems that can sense their physical environment, and
adapt their behavior accordingly. In this paper we seek to develop a systematic understanding of context-aware computing by
constructing a formal model and notation for expressing context-aware computations. This discussion is followed by a
description and comparison of current context modeling and reasoning techniques.
Taking Action Implementing Effective Mathematics Teaching Practices in Grades...Ely Hernandez
This document describes the beginning of a high school mathematics lesson on statistics and modeling. The teacher engages students by connecting the lesson topic to bungee jumping. Students watch a video of an actual bungee jump and discuss factors that affect the jump. Working in groups, students then conduct an experiment dropping a Barbie doll with varying numbers of rubber bands to model a bungee jump and collect data to analyze. The teacher monitors student work to ensure they are carrying out the experiment correctly.
Este documento presenta una introducción al campo de la Investigación Educativa. Describe cómo la investigación ha ido influyendo gradualmente en las ideas y prácticas educativas. Señala que la investigación educativa es un estudio científico y sistemático que utiliza métodos cualitativos y cuantitativos. Explica que los investigadores realizan diferentes tipos de estudios - básicos, aplicados y evaluativos - con distintos propósitos. Finalmente, introduce algunos conceptos y procesos fundamentales de la investigación educativa, como la identific
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This document describes a proposed content-based image retrieval system using backpropagation neural networks (BPNN) and k-means clustering. It begins by discussing CBIR techniques and features like color, texture, and shape. It then outlines the proposed system which includes training a BPNN on image features, validating images, and testing by querying and retrieving similar images. Performance is analyzed based on metrics like accuracy, efficiency, and classification rate. Results show the system achieves up to 98% classification accuracy within 5-6 seconds.
This document outlines Serena Pollastri's year 1 research plan. The research aims to map visualization processes that can contribute to designing future scenarios of sustainable, livable cities. The theoretical framework is based on a "metadesign" approach of collaboratively designing design tools to enable systemic change. The research structure involves literature reviews on visualizations, future scenarios, and cities/liveability. Design experiments are planned, including future visioning workshops and a foresight report. The timeline shows literature reviews and design experiments occurring through 2014-2016, culminating in publications and conferences.
Visualizer for concept relations in an automatic meaning extraction systemPatricia Tavares Boralli
This document discusses a visualizer interface that has been developed for an automatic meaning extraction (AME) system. The visualizer allows users to view concepts and their relationships extracted from text documents in a graph format. It maps concepts as nodes and relationships as edges. Users can search for concepts, view related concepts, and trace relationships back to the original text passages. The visualizer was created to help users interact with and understand the outputs of the AME system, which automatically extracts concepts and relations from documents across various domains.
This document discusses semantic networks and their applications in artificial intelligence. It begins with describing how semantic networks originated in psychology for analyzing relationships between concepts, and were later adopted by AI to analyze textual data. Key applications of semantic networks discussed include idea generation, visual text analysis, and conceptual design. The document also provides historical background on semantic networks and how they are used for knowledge representation.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
Speed has become a way of life. We are asymptotically piling data. Speed can be achieved with new design
processes, techniques, and Technology. Innovations AR and VR are just some of the many forms of
technologies that will play a key role in shaping the Architecture and Planning of tomorrow, making it
future-ready and ushering in a new age of innovation. AR and VR in Architecture & Planning were
introduced as assisting tools and has helped generate multiple design options, expanded possibilities of
visualization, and provided us with more enhanced, detailed, and specific experience in real-time; enabling
us to see the resultsof work on hand well before the commencement of the project. These tools are further
developed for city development decisions, helping citizens interact with local authorities, access public
services, and plan their commute. After reviewing multiple research papers, it had been observed that each
one is moving forward with the changes brought by it, without entirely understanding its role. This paper
provides a summary of theappliance of AR & VR in architecture and planning.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
Speed has become a way of life. We are asymptotically piling data. Speed can be achieved with new design
processes, techniques, and Technology. Innovations AR and VR are just some of the many forms of
technologies that will play a key role in shaping the Architecture and Planning of tomorrow, making it
future-ready and ushering in a new age of innovation. AR and VR in Architecture & Planning were
introduced as assisting tools and has helped generate multiple design options, expanded possibilities of
visualization, and provided us with more enhanced, detailed, and specific experience in real-time; enabling
us to see the resultsof work on hand well before the commencement of the project. These tools are further
developed for city development decisions, helping citizens interact with local authorities, access public
services, and plan their commute. After reviewing multiple research papers, it had been observed that each
one is moving forward with the changes brought by it, without entirely understanding its role. This paper
provides a summary of theappliance of AR & VR in architecture and planning.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
Speed has become a way of life. We are asymptotically piling data. Speed can be achieved with new design
processes, techniques, and Technology. Innovations AR and VR are just some of the many forms of
technologies that will play a key role in shaping the Architecture and Planning of tomorrow, making it
future-ready and ushering in a new age of innovation. AR and VR in Architecture & Planning were
introduced as assisting tools and has helped generate multiple design options, expanded possibilities of
visualization, and provided us with more enhanced, detailed, and specific experience in real-time; enabling
us to see the resultsof work on hand well before the commencement of the project. These tools are further
developed for city development decisions, helping citizens interact with local authorities, access public
services, and plan their commute. After reviewing multiple research papers, it had been observed that each
one is moving forward with the changes brought by it, without entirely understanding its role. This paper
provides a summary of theappliance of AR & VR in architecture and planning.
FUTURISTIC TECHNOLOGY IN ARCHITECTURE & PLANNING - AUGMENTED AND VIRTUAL REAL...ijscai
This document provides an overview of augmented reality (AR) and virtual reality (VR) technologies and their applications in architecture and urban planning. It first discusses how AR and VR have helped generate multiple design options, improve visualization, and provide more detailed virtual experiences of projects before they are built. It then reviews several research papers on the topics of AR/VR in design. Key applications discussed include enabling better collaboration and ideation, analyzing spatial relationships, and allowing public involvement in design decisions. The document also outlines some challenges to wider adoption of these technologies, such as technical limitations of equipment and the need for more specialized tools tailored for the design field.
This document proposes a data model for managing large point cloud data while integrating semantics. It presents a conceptual model composed of three interconnected meta-models to efficiently store and manage point cloud data, and allow the injection of semantics. A prototype is implemented using Python and PostgreSQL to combine semantic and spatial concepts for queries on indoor point cloud data captured with a terrestrial laser scanner.
This document presents a content-based image retrieval semantic model for shaped and unshaped objects. It proposes classifying objects into two categories: shaped objects with a fixed shape like animals and objects, and unshaped objects without a fixed shape like landscapes. For unshaped objects, local regions are classified by frequency of occurrence and semantic concepts are evaluated using color, shape, and regional dissimilarity factors. For shaped objects, semantic concepts are measured using normalized color, edge detection, particle removal, and shape similarity. Several existing content-based image retrieval techniques are also briefly discussed.
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A novel Image Retrieval System using an effective region based shape represen...CSCJournals
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International Journal of Computational Engineering Research(IJCER)ijceronline
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Context-aware computing refers to a general class of mobile systems that can sense their physical environment, and
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description and comparison of current context modeling and reasoning techniques.
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Este documento presenta una introducción al campo de la Investigación Educativa. Describe cómo la investigación ha ido influyendo gradualmente en las ideas y prácticas educativas. Señala que la investigación educativa es un estudio científico y sistemático que utiliza métodos cualitativos y cuantitativos. Explica que los investigadores realizan diferentes tipos de estudios - básicos, aplicados y evaluativos - con distintos propósitos. Finalmente, introduce algunos conceptos y procesos fundamentales de la investigación educativa, como la identific
O documento discute os desafios da sustentabilidade no setor de alimentos. A produção de alimentos precisa crescer para alimentar uma população crescente, mas isso coloca pressão sobre os recursos naturais e contribui para as mudanças climáticas. Soluções como agricultura regenerativa, redução do desperdício de alimentos e dietas à base de plantas podem ajudar a enfrentar esses desafios de forma sustentável.
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La Unión Europea ha acordado un embargo petrolero contra Rusia en respuesta a la invasión de Ucrania. El embargo prohibirá las importaciones marítimas de petróleo ruso a la UE y pondrá fin a las entregas a través de oleoductos dentro de seis meses. Esta medida forma parte de un sexto paquete de sanciones de la UE destinadas a aumentar la presión económica sobre Moscú y privar al Kremlin de fondos para financiar su guerra.
La Unión Europea ha propuesto un nuevo paquete de sanciones contra Rusia que incluye un embargo al petróleo. El embargo prohibiría las importaciones de petróleo ruso por mar y por oleoducto, aunque se concederían exenciones temporales a Hungría y Eslovaquia. Este sería el sexto paquete de sanciones de la UE contra Rusia desde la invasión de Ucrania a finales de febrero.
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1. See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/228602445
Semantic Visualisation in Design Computing
Article · August 2000
DOI: 10.1061/40513(279)117
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2. Semantic visualisation in design computing
SIMEON J. SIMOFF AND MARY LOU MAHER
Key Centre of Design Computing and Cognition
University of Sydney, NSW 2006, Australia
simeon, mary@arch.usyd.edu.au
Abstract: In this paper we discuss the issues of visualisation in architectural design and civil engineering
in the broader sense. Usually the term "visualisation" in these fields is connected with 3D modeling and
photorealism of physical objects. Another part of the research community understands visualisation as
the visual representation of numerical data, popular in the field of data mining and scientific
visualisation. In this paper, we present a common approach for designing visualisation schemes that
leverage pre-arranged semantics. The approach is based on a combination of the models of the metaphor
in cognitive linguistics and the form-semantics-function categorisation. The use and development of
metaphors is still handcrafted rather than based on formal methods. Our framework includes evaluation of
the metaphor mapping.
Introduction
Visualisation, in broad sense, is the conversion of data into figures. This spans the area from
simple 2D bar graphs and function curves to sophisticated graphical interaction in 3D
virtual worlds and virtual reality systems. The latter are increasingly employed in design due
to their emphasis on visualisation of geometry. From another point of view visualisation is
a method of extracting meaningful information from complex objects using interactive
graphics and imaging. In this case, through the means of visualisation techniques, data is
converted into a consistent and, to some extent, compact graphical form, so that the
observer can comprehend the knowledge and information in the data. Thus, visualisation, a
process of mapping data onto visual dimensions to create a visual representation, is a key
part of both data mining and virtual design paradigms.
In data mining, semantic visualisation can assist investigators to gain new insights
from analysed data through the semantics of the visual form in which the data in presented.
In computer-supported collaborative design environments, visualisation establishes the
connection between the intended functionality of an object and the semantics of its form.
For instance, the tools supporting conference activities in a conference room in the Virtual
Campus at the University of Sydney have been assigned rectangular forms with a particular
color code (Maher et al., 1999). In both cases, visualisation establishes the semantic
connection between the form and the function associated with this form.
Design computing in architecture and civil engineering operates with an extensive
amount of geometrical data. The geometric objects that are usually displayed and
manipulated by CAD, 3D modelling and photorealism systems are the digital
representations of the form of the objects that we model. For example, in architectural
CAD, the 3D model of an arch looks like an arch. We also label it as an "arch" - a word
that has particular meaning to us. The purpose, or the functionality of this arch can be
different, depending on the context in which the model is used. If the model simulates part
of physical reality - for example, a section of a bridge, then the function of the arch in that
model is defined by the functionality of the modelled object from which the arch is part of.
If the arch is an object within a virtual world, its functionality may have little in common
with the functionality of physical arches in the engineering sense. For example, an arch in a
virtual world can functionally be a gateway for taking an automated navigation path
through a design project.
3. We define semantic visualisation as a visualisation method, which establishes and
preserves the semantic link between form and function in the context of the visualisation
metaphor. Establishing a connection between form and functionality is not a trivial part of
the design process. In a similar way, selecting the appropriate form for representing data
graphically, whether the data consists of numbers or text, is not a straightforward procedure
- the numbers or the text descriptions don't have a natural visual representation. On the
other hand, how data are represented visually has a powerful effect on how the structure and
hidden semantics in the data is perceived and understood.
We consider semantic visualisation for two derivatives of visualisation -
visibilisation and visistraction (Choras and Steinmann, 1995). Visibilisation is visualisation
focusing on the presentation and interpretation which complies with rigorous mapping
from physical reality. By contrast, visistraction is the visualisation of abstract concepts and
phenomena, which do not have a direct physical interpretation or analogy. Visibilisation
has the potential to bring key insights, by emphasising aspects that were unseen before. The
dynamic visualisation of the heat transfer during the design of the heat-dissipating tiles
cover of the underside of the space-shuttle is an early example of the application of
visibilisation (Gore, 1981). Visistracton can give a graphic depiction of intuition regarding
objects and relationships. The 4D simulation of data flow is an example of visistraction,
which provides insights impossible without it. In a case-base reasoning system, visistraction
techniques can be used to trace the change of relationships between different concepts with
the addition of new cases.
Both kinds of visualisation play an important role in design computing. However,
semantic visualisation remains a hand crafted methodology, where each case is considered
separately. In this paper, we present an approach to semantic visualisation based on a
cognitive model of metaphors, metaphor formalisation and evaluation. We illustrate the
application of this approach with examples from visistraction of design communication
data and visibilisation of virtual worlds.
Form - Semantics - Function: a formal approach towards constructing and
evaluating visualisation techniques for design computing.
In semantic visualisation, we consider the form, semantics, and function of the objects used
for visualisation of data. We present an approach to semantic visualisation based on:
• Metaphor analysis
• Metaphor formalisation
• Metaphor evaluation.
We draw our examples from visistraction, the visualisation techniques used to understand
the results of data mining collaborative design sessions, and visibilisation, the visualisation
of function in virtual worlds based on physical forms that have a similar function.
METAPHOR ANALYSIS
During metaphor analysis, the content of the metaphor is established. In the use of
metaphor in cognitive linguistics, the terms source and target to refer to the conceptual
spaces connected by the metaphor. The target is the conceptual space that is being
described, and the source is the space that is being used to describe the targeti
. In this
mapping the structure of the source domain is projected onto the target domain in a way
that is consistent with inherent target domain structure (Lakoff, 1993), (Turner, 1994). In
i
In the research literature the target is variously referred to as the primary system or the topic, and the
source is often called the secondary system or the vehicle.
4. the context of semantic visualisation, the consistent use of metaphor is expected to bring
an understanding of a relatively abstract and unstructured domain in terms of more concrete
and structured visual elements through the visualisation schemata.
An extension of the source-target mapping, proposed by (Turner and Fauconnier,
1995) includes the notion of generic space and blend space. Generic space contains the
skeletal structure that applies to both source and target spaces. The blend space often
includes structure not projected to it from either space, namely emergent structure on its
own. The ideas and inspirations developed in the blend space can lead to modification of
the initial input spaces and change the knowledge about those spaces, i.e. to change and
evolve the metaphor. The process is called conceptual blending - it is the essence in the
development of semantic visualisation techniques.
In our approach we combine the form-semantics-function categorisation of the
objects being visualised with the Turner and Fauconnier (1995) model. The form of an
object can express the semantics of that object, that is, the form can communicate implicit
meaning understood through our experiences with that form. From the form in the source
space we can connect to a function in the target space via the semantics of the form. The
resultant model is shown in Figure 1, a particular case of the Turner and Fauconnier (1995)
model applied to the visualisation of collaborative design data.
• Participation
• Topic of discussion
• correspondance between visual
assymmetry and intensity of
participation
• correspondance between visual
balance and design communication
categories
• Symmetry
• Balance
• Proportion
• Polygon
• Segment
• Circle
Blended space:
NEW
SEMANTICS
Blended space:
NEW
SEMANTICS
Target space:
FUNCTION
Target space:
FUNCTION
Generic space:
COMMON
SEMANTICS
Generic space:
COMMON
SEMANTICS
Source space:
FORM
Source space:
FORM
Figure 1. Metaphor analysis applied to the visualisation of collaborative design data.
The source space in this case is the space of 2D and 3D geometric shapes. The
target space includes the concepts associated with the functions that we find in analysing a
collaborative design session. The transfer of semantics has two components - the common
semantics, which is carried by notions that are valid in both domains and what we call new
semantics - the blend, which establishes the unique characteristics revealed by the
correspondence between the form metaphor and functional characteristics of that form.
The schema illustrates how metaphorical inferences produce parallel knowledge structures.
The examples in the boxes under each space in Figure 1 are illustrated in Figure 2, which
shows a visualisation of the results of data mining from a collaborative session in a text-
based 3D virtual world. The discussion was one of many meetings of a design team in Active
Worlds, a 3D collaborative modelling environment. The design project was the interior
layout of a global learning building on the Stanford University campus. The data was
categorised using a design communication coding scheme developed by Gabriel and Maher
(1999). The visual metaphor of a polygon shape provides a mapping from the amount of
utterances for each participant to a distance from a central point to the corresponding
5. vertex of the polygon. The visual metaphor of a pie shape provides a mapping from the
amount of discussion in each category to a proportion of the pie. The semantics of the
polygon and the pie shape convey proportion and relative amounts. In Figure 2a the
function each portion is mapped to in the target domain is the participant, when in Figure
2b and c this function is the topic of the discussion. Without reading the specific numbers, a
person can easily see that the project coordinator, together with designer's 1, 3 and 5, were
the most active participants. And, the majority of the discussion was in the category of
design communication, with a high proportion of discussion about task/instruction,
introduction of ideas, and clarification of ideas. Additionally, it is implicit in the pie
visualisation that the sum of all categories of discussion is 100%, that is, each statement
was assigned only one category.
Project Coordiator
Team Manager
Designer 1
Designer 2
Designer 3
Designer 4
Designer 5
Designer 6
Communication
control
17%
Communication
Technology
3%
Navigation
6%
Design
Communication
67%
Social
communication
7%
Evaluation of idea
7%
Low-level design
6%
High-level design
14%
Brief
5%
Schedule
2%
Task/Instruction
17%
Refinement of idea
8%
Clarification of idea
20%
Acceptance of
idea
1%
Rejection of idea
4%
Introduction of idea
16%
a. Individual participation b. Communication categories c. Design communication
Figure 2. Polygon shape visistraction of individual participation in team meeting and pie shape
visistraction of categories and amounts of communication in team meeting.
METAPHOR FORMALISATION
Metaphor formalisation in the design of semantic visualisation schemes includes the
following basic steps:
• Identification of the source and target spaces of the metaphor - the class of forms and
the class of features or functions that these forms will represent. In the data mining of
collaborative design discussions, this involves identifying the forms and the semantics
that facilitate the visualisation of specific functions in the discussions. In the
visualisation of virtual environments, this involves identifying the classes of forms of
physical objects that will facilitate the understanding of functions of the virtual
environments.
• Conceptual decomposition of the source and target spaces produces the set of concepts
that describe both sides of the metaphor mapping. As a rule, metaphorical mappings do
not occur isolated from one another. They are sometimes organized in hierarchical
structures, in which `lower' mappings in the hierarchy inherit the structures of the
`higher' mappings. In other words, this means that visualisation schemes, which use
metaphor are expected to preserve the hierarchical structures of the data that they
display. In visistraction, these are the geometric characteristics of the forms from the
source space, and other form attributes like colours, line thickness, shading, etc. and the
set of functions and features in the target space associated with these attributes and
variations.
• Identifying the dimensions of the metaphor along which the metaphor operates. These
dimensions constitute the common semantics. In visistraction this can be for instance
key properties of the form, like symmetry and balance with respect to the center of
gravity, that transfer semantics to the corresponding functional elements in the target
domain. In the visualisation of virtual environments, these dimensions may act as
6. constraints - for example, only the predefined elements with those geometrical
properties can be used as the building blocks.
• Establishing semantic links, relations and transformations between the concepts in both
spaces, creating a resemblance between the forms in the source domain and the
functions in the target domain.
METAPHOR EVALUATION
In this section, we discuss the issues related to the evaluation of the visualisation. In spite of
the large number of papers describing the use of the metaphor in the design of computer
interfaces and virtual environments, there is a lack of formal evaluation. We have tailored
the Anderson et al. (1994) model for investigating the metaphor mapping to meet our
form-semantics-function formalism. The model is presented in Figure 3.
V- F+ V+ F+
V+ F-
Figure 3. Model for evaluating metaphor mapping (based on (Anderson et al., 1994) )
The "V" and "F" are labels for visualisation and function features, respectively. The
"VF" label with indices denotes numbers of features, namely:
• +
+ F
V - function features that are mapped to the visualisation schema;
• +
− F
V - function features that are not supported by the visualisation schema;
• −
+ F
V - features in the visualisation schema, not mapped to the functional
features.
The ratio
+
+
+
−
F
V
F
V
provides an estimate of the quality of the metaphor used for the
visualisation - the smaller the better. We illustrate the idea by evaluating examples of
semantic visualisation of textual data and objects in virtual environments. In the first
example, we consider two different forms for visualising the same set of functional features.
In the second example we consider one form for conveying two different set of features.
The role of visistraction in concept relationship analyis is to assist the discovery of
the relationship between concepts, as reflected in the available text data. The analysis uses
word frequencies, their co-occurence and other statistics, and cluster analysis procedures.
We investigate two visual metaphors - "Euclidian space" and "Tree", which provide a
mapping from the numerical statistics and cluster analysis data into the target space (see
Figure 1) of concepts and relations between them. The visualisation features for both
metaphors and the function features of the target space are shown in Table 1. Examples of
the two visualisation metaphors are shown in Figure 4. The example of Euclidian space
metaphor, shown in Figure 4a, maps the statistics of words to coordinates of points in
2D/3D space. The blending semantics is the degree to which the terms are related to each
other can be perceived visually from the distance between the corresponding data points -
the closer the points the tighter is the relationship between the words. However, it is
7. difficult to make a steady judgement about what the relation is and whether we deal with
complex terms. The distance to the surface, proportional to the frequency of the words can
convey the message that a word is a key word. However, there is no feature in the
visualisation, which shows context links between words, the strength of this links and other
relations between words.
Table 1. Visualisation and function features
Visualisation features
of Euclidian space
metaphor
Visualisation features of
tree metaphor
Function features
- point
- alphanumeric single-
word point labels
- axes
- plane
- color
- line segment
- nodes
- alphanumeric multi-word node
labels
- signs "+" and "-"
- branches
- numeric labels for branches
- simple/complex concept
- subject key word
- hierarchical relationship
- context link
- link strength
- synonymy
- hyponymy
a. 10 most frequent words in the description of lateral load resisiting system in one of the wide-span
building cases
ii
Part of a semantic net
iii
for the term "load resisting system".
Figure 4. Visistraction ualisation of the results of cluster analysis performed over a text data set
iv
ii
CATPAC by Provalis Research Co.
iii
TextAnalyst by Megaputer Intelligence, Inc.
iv
The source text comes from the SAM (Structure and Materials) case library available at
http://www.arch.usyd.edu.au/kcdc/caut/
8. The example of a tree metaphor, shown in Figure 4b, maps the statistics of words to
a topological structure of linked nodes. This visistaction includes nodes with single- and
multiple-word labels, numeric values of each link between terms and the weight of the term
among the other terms in the tree. The results of the comparison between the two
metaphors are presented in Table 2 and Table 3. The Euclidean space metaphor has a poor
performance for visistraction of concept relationships.
Table 2. Visualisation support for function features in Euclidean space and tree metaphors
Function features Support by the
Euclidean space
metaphor
Support by the Tree
metaphor
Simple/complex concept - +
Subject key word + +
Hierarchical relationship - +
Context link - +
Link strength - +
Synonymy - -
Hyponymy - -
Table 3. Comparison of in Euclidean space and tree metaphors
Euclidean space
metaphor
Tree metaphor
+
+ F
V 1 5
+
− F
V 6 2
+
+
+
−
F
V
F
V 6 0.4
The other example of metaphor evaluation is connected with semantic visualisation
of virtual environments. An example of visualisation and functional features under
consideration is given in Table 4. In visualisation of virtual environments, we distinguish
two cases:
• The virtual environment is used to visualise the elements of a design which is
intended to be constructed physically, a visual simulation of a physical system.
In this case we have a "thick" layer of common semantics in the face of the
physical laws that establish the current limits of the functionality and a fairly
thin blend space. The case presented in Figure 5a is a fragment of the virtual
design of Stanford University Learning Lab. The arch is part of a building, which
imples that it is intended to carry part of the load in the facade.
• The virtual environment is functional without being constructed physically, as
in virtual worlds. The arches in Figure 5b provide a visualisation of the entrance
to information about architectural design styles in an Active Worlds universe.
The arch form is used as a gateway towards particular part of the environment,
providing perspective view and connection to the corresponding topic.
Table 4. Visualisation and function features
Visualisation
features
Fuction features in virtual
environment for physical
simulation
Function features in virtual
environment
- geometry
- size
- color
- texture
- carrying load in the building
- providing space under it
- providing gateway to other
parts in the environment
- providing view to a
background information
9. a. b.
Figure 5. Visualisation in a virtual design environment
v
Conclusions
The quality of the information presented to a designer during a design session is directly
related to the facility in understanding the semantics of the data. Semantic visualisation can
improve the quality of the presentation of large amounts of information. Visualisation, if
used in an appropriate way, offers considerable semantic compression of presented
information.
We present an approach for constructing semantic visualisation schemes, based on a
metaphorical mapping in terms of form, semantics and functionality. We also illustrate the
use of the approach for the selection of appropriate visualisation support in text data
mining and semantic navigation in virtual design environments.
Acknowledgements
This research work is partially funded by the Australian Research Council
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