The WebML innovation cycle

•Transferir como PPTX, PDF•

1 gostou•1,468 visualizações

Marco Brambilla

10 years of WebRatio is a good occasion for thinking about the path that led from a university research project to a recognized modeling language (WebML) and a solid, industrialized version of a toolsuite (WebRatio). The main ingredient of our history are basically: - a substrate for cross-fertilization coming from European Research projects (W3I3, WebSI, Cooper, BPM4People, ...) - valuable inputs and requirements from customers (both final customers and software integrators) - a strong research team that continuously worked on innovating the approach - the teaching activities within the university - and the professional developers and analysts at Web Models that work hard for making a good product out of the rough ideas and experiments produced in the university. These ingredients allowed more than 10 years of evolution of the language and the tool. I tried to summarized this in the virtuous cycle of our experience. While research provides innovation to both teaching and industrialization, and finally produces the upto date version of the language and methodology. The tool vendor provides the tool itself and also requirements coming from real industrial customers. The tool is extremely useful for teaching and research purposes not only within our group, but throughout the world (thanks to an academic program that allows education institutions to get free licenses of the tool). The role of customer is crucial in this picture, because it's from their input (business, technical and UI requirements) that we extract the actual needs of the industry. The whole innovation cycle start there. Furthermore, customers provide feedback and feasibility/acceptability check upon our findings and solutions. This virtuous cycle has been able to carry the core idea of the WebML language through 10 years of history in the product (and 15 years of history of the language). The lesson learned is that, if you have a core concept which is flexible and innovable, a good strategy can lead to continuous evolution, improvement and expansion of the idea. In these years the language underwent a huge number of incremental additions: support of web services support of business processes support of semantic web features support of RIA - AJAX features If you want to get a flavour of the experience, you may check out this paper, published in John Mylopoulos Festschrift by Springer:S. Ceri, M. Brambilla, P. Fraternali: “The History of WebML Lessons Learned from 10 Years of Model-Driven Development of Web Applications“. In book: Conceptual Modeling: Foundations and Applications, Essays in honor of John Mylopoulos, Springer LNCS, Festschrift series, vol. 5600, 2009, pp. 273-292

Tecnologia Educação

WebML WebML 10 (or 15?) years, without showing it Marco Brambilla Politecnico di Milano marco.brambilla@polimi.itmarcobrambimarcobrambi

Agenda ,[object Object]

The strategy

The history,[object Object]

The need Conceptual modeling Abstraction from the technology .. But NOT From the technological opportunities From the requirements Innovation Extensibility

The Strategy Virtuous innovation cycle

The Strategy Retrospective Virtuous Cycle At two levels: Macro-innovations Refinement of each innovation Repeatability of the experience.. Not granted!

innovation Research (Politecnico) Tool vendor (WebRatio) Toolsuite, industrial requirements Teaching (university courses) innovation toolsuite WebML Design method, language, and platform innovation Customers (requirement providers) requirements use cases Final customers (EU) Research Project consortia Software houses and integrators

The history “Amarcord”? (F. Fellini, 1973)

1. AutoWeb Once upon a time ... 1998 W3I3 project The research starts

2. WebML And then ... 1999 Teaching and consolidation at Politecnico

3. WebML in action And then ... 2000 The first “customer”

3. WebML in action And then ... 2000 The first “customer” No company or product yet Features implemented at night in Italy upon customers request in the US during the day 

4. Web Services And then ... 2003 SOA, Services, Mashups First research solution:

4. Web Services And then ... 2005 Refinement and implementation

5. Business Processes And then ... 2004 Business processes andorchestrations Research proposal:

5. Business Processes And then ... 2010 Industrial implementation and refinement Directly in the WebRatio tool After a few years (based on customers need)

6. Semantic Web And then ... 2005

6. Semantic Web Still a research project only But.. What about the future? Linked data, ...

7. RIA - AJAX And then ... 2005 Rich Web interfaces Theoretical model in the research group And simplified model implemented in the tool immediately available Future: a new, comprehensive model coming up

8. Social Web / BPM Today

8. Social Web / BPM Oggi

9. Standardization Today Strategic effort within OMG (Object Management Group)

9. ... What about the future? Search, Interfaces, Modernization And...?

Mais conteúdo relacionado

Mais de Marco Brambilla

Thesis Topics and Proposals @ Polimi Data Science Lab - 2023 - prof. Brambill...

Thesis Topics and Proposals @ Polimi Data Science Lab - 2023 - prof. Brambill...

Thesis Topics and Proposals @ Polimi Data Science Lab - 2023 - prof. Brambill...

Marco Brambilla

We discuss the use of hierarchical transformers for user semantic similarity in the context of analyzing users' behavior and profiling social media users. The objectives of the research include finding the best model for computing semantic user similarity, exploring the use of transformer-based models, and evaluating whether the embeddings reflect the desired similarity concept and can be used for other tasks. We use a large dataset of Twitter users and apply an automatic labeling approach. The dataset consists of English tweets posted in November and December 2020, totaling about 27GB of compressed data. Preprocessing steps include filtering out short texts, cleaning user connections, and selecting a benchmark set of users for evaluation. Since Transformer architectures are known to work well on short text, we cannot use them on extensive collections of tweets describing the activity of a user. Therefore, we propose a hierarchical structure of transformer models to be used first on tweets and then on their aggregations. The models used in the study include hierarchical transformers, and the tweet embeddings are obtained using four Transformer-based models: RoBERTa2, BERTweet3, Sentence BERT4, and Twitter4SSE5. The researchers test different techniques for processing tweet embeddings to generate accurate user embeddings, including mean pooling, recurrence over BERT (RoBERT), and transformer over BERT (ToBERT). The evaluation of the models is done on a set of 5,000 users, comparing user similarities with 30 other candidate users, 5 of which are considered similar and 25 considered dissimilar. The evaluation metrics used include mean average precision (MAP), mean reciprocal rank (MRR) at 10, and normalized discounted cumulative gain (nDCG). The optimization process involves selecting a loss function and using the AdamW optimizer with specific hyperparameters. The results show that the hierarchical approach with a Stage-1 Twitter4SSE model and a Stage-2 Transformer model performs the best among the alternatives. In conclusion, the research provides a large unbiased dataset for user similarity analysis, presents a hierarchical language model optimized for accurate user similarity computation, and validates the models' performance on similarity tasks, with potential applications to related problems. The future work includes investigating the impact of time and topic drift on the models' performance.

Hierarchical Transformers for User Semantic Similarity - ICWE 2023

Hierarchical Transformers for User Semantic Similarity - ICWE 2023

Hierarchical Transformers for User Semantic Similarity - ICWE 2023

Marco Brambilla

The Web and social media are the environments where people post their content, opinions, activities, and resources. Therefore, a considerable amount of user-generated content is produced every day for a wide variety of purposes. On the other side, people live their everyday life immersed in the physical world, where society, economy, politics and personal relations continuously evolve. These two opposite and complementary environment are today fully integrated: they reflect each other and they interact with each other in a stronger and stronger way. Exploring and studying content and data coming from both environments offers a great opportunity to understand the ever evolving modern society, in terms of topics of interest, events, relations, and behaviour. In this speech I will discuss through business cases and socio-political scenarios how we can extract insights and understand reality by combining and analyzing data from the digital and physical world, so as to reach a better overall picture of reality itself. Along this path, we need to keep into account that reality is complex and varies in time, space and along many other dimensions, including societal and economic variables. The speech highlights the main challenges that need to be addressed and outlines some data science strategies that can be applied to tackle these specific challenges. This slide deck has been presented as a keynote speech at WISE 2022 in Biarritz, France.

Exploring the Bi-verse.A trip across the digital and physical ecospheres

Exploring the Bi-verse.A trip across the digital and physical ecospheres

Exploring the Bi-verse.A trip across the digital and physical ecospheres

Marco Brambilla

In online social media platforms, users can express their ideas by posting original content or by adding comments and responses to existing posts, thus generating virtual discussions and conversations. Studying these conversations is essential for understanding the online communication behavior of users. This study proposes a novel approach to retrieve popular patterns on online conversations using network-based analysis. The analysis consists of two main stages: intent analysis and network generation. Users’ intention is detected using keyword-based categorization of posts and comments, integrated with classification through Naïve Bayes and Support Vector Machine algorithms for uncategorized comments. A continuous human-in-the-loop approach further improves the keyword-based classification. To build and understand communication patterns among the users, we build conversation graphs starting from the hierarchical structure of posts and comments, using a directed multigraph network. The experiments categorize 90% comments with 98% accuracy on a real social media dataset. The model then identifies relevant patterns in terms of shape and content; and finally determines the relevance and frequency of the patterns. Results show that the most popular online discussion patterns obtained from conversation graphs resemble real-life interactions and communication.

Conversation graphs in Online Social Media

Conversation graphs in Online Social Media

Conversation graphs in Online Social Media

Marco Brambilla

Trigger.eu: Cocteau game for policy making - introduction and demo

Trigger.eu: Cocteau game for policy making - introduction and demo

Trigger.eu: Cocteau game for policy making - introduction and demo

Marco Brambilla

A large audience of users and typically a long time frame are needed to produce sensible and useful log data, making it an expensive task. To address this limit, we propose a method that focuses on the generation of REALISTIC NAVIGATIONAL PATHS, i.e., web logs . Our approach is extremely relevant because it can at the same time tackle the problem of lack of publicly available data about web navigation logs, and also be adopted in industry for AUTOMATIC GENERATION OF REALISTIC TEST SETTINGS of Web sites yet to be deployed. The generation has been implemented using deep learning methods for generating more realistic navigation activities, namely Recurrent Neural Network, which are very well suited to temporally evolving data Generative Adversarial Network: neural networks aimed at generating new data, such as images or text, very similar to the original ones and sometimes indistinguishable from them, that have become increasingly popular in recent years. We run experiments using open data sets of weblogs as training, and we run tests for assessing the performance of the methods. Results in generating new weblog data are quite good with respect to the two evaluation metrics adopted (BLEU and Human evaluation). Our study is described in detail in the paper published at ICWE 2020 – International Conference on Web Engineering with DOI: 10.1007/978-3-030-50578-3. It’s available online on the Springer Web site.

Generation of Realistic Navigation Paths for Web Site Testing using RNNs and ...

Generation of Realistic Navigation Paths for Web Site Testing using RNNs and ...

Generation of Realistic Navigation Paths for Web Site Testing using RNNs and ...

Marco Brambilla

The network of collaborations in an open source project can reveal relevant emergent properties that influence its prospects of success. In this work, we analyze open source projects to determine whether they exhibit a rich-club behavior, i.e., a phenomenon where contributors with a high number of collaborations (i.e., strongly connected within the collaboration network) are likely to cooperate with other well-connected individuals. The presence or absence of a rich-club has an impact on the sustainability and robustness of the project. For this analysis, we build and study a dataset with the 100 most popular projects in GitHub, exploiting connectivity patterns in the graph structure of collaborations that arise from commits, issues and pull requests. Results show that rich-club behavior is present in all the projects, but only few of them have an evident club structure. We compute coefficients both for single source graphs and the overall interaction graph, showing that rich-club behavior varies across different layers of software development. We provide possible explanations of our results, as well as implications for further analysis.

Analyzing rich club behavior in open source projects

Analyzing rich club behavior in open source projects

Analyzing rich club behavior in open source projects

Marco Brambilla

Analysis of On-line Debate on Long-Running Political Phenomena.The Brexit C...

Analysis of On-line Debate on Long-Running Political Phenomena.The Brexit C...

Analysis of On-line Debate on Long-Running Political Phenomena.The Brexit C...

Marco Brambilla

In a world more and more connected, new and complex interaction patterns can be extracted in the communication between people. This is extremely valuable for brands that can better understand the interests of users and the trends on social media to better target their products. In this paper, we aim to analyze the communities that arise around commercial brands on social networks to understand the meaning of similarity, collaboration, and interaction among users.We exploit the network that builds around the brands by encoding it into a graph model.We build a social network graph, considering user nodes and friendship relations; then we compare it with a heterogeneous graph model, where also posts and hashtags are considered as nodes and connected to the different node types; we finally build also a reduced network, generated by inducing direct user-to-user connections through the intermediate nodes (posts and hashtags). These different variants are encoded using graph representation learning, which generates a numerical vector for each node. Machine learning techniques are applied to these vectors to extract valuable insights for each user and for the communities they belong to. In the paper, we report on our experiments performed on an emerging fashion brand on Instagram, and we show that our approach is able to discriminate potential customers for the brand, and to highlight meaningful sub-communities composed by users that share the same kind of content on social networks.

Community analysis using graph representation learning on social networks

Community analysis using graph representation learning on social networks

Community analysis using graph representation learning on social networks

Marco Brambilla

Available Data Science M.Sc. Thesis Proposals

Available Data Science M.Sc. Thesis Proposals

Available Data Science M.Sc. Thesis Proposals

Marco Brambilla

Social media platforms let users share their opinions through textual or multimedia content. In many settings, this becomes a valuable source of knowledge that can be exploited for specific business objectives. Brands and companies often ask to monitor social media as sources for understanding the stance, opinion, and sentiment of their customers, audience and potential audience. This is crucial for them because it let them understand the trends and future commercial and marketing opportunities. However, all this relies on a solid and reliable data collection phase, that grants that all the analyses, extractions and predictions are applied on clean, solid and focused data. Indeed, the typical topic-based collection of social media content performed through keyword-based search typically entails very noisy results. We recently implemented a simple study aiming at cleaning the data collected from social content, within specific domains or related to given topics of interest. We propose a basic method for data cleaning and removal of off-topic content based on supervised machine learning techniques, i.e. classification, over data collected from social media platforms based on keywords regarding a specific topic. We define a general method for this and then we validate it through an experiment of data extraction from Twitter, with respect to a set of famous cultural institutions in Italy, including theaters, museums, and other venues. For this case, we collaborated with domain experts to label the dataset, and then we evaluated and compared the performance of classifiers that are trained with different feature extraction strategies.

Data Cleaning for social media knowledge extraction

Data Cleaning for social media knowledge extraction

Data Cleaning for social media knowledge extraction

Marco Brambilla

Knowledge in the world continuously evolves, and ontologies are largely incomplete, especially regarding data belonging to the so-called long tail. We propose a method for discovering emerging knowledge by extracting it from social content. Once initialized by domain experts, the method is capable of finding relevant entities by means of a mixed syntactic-semantic method. The method uses seeds, i.e. prototypes of emerging entities provided by experts, for generating candidates; then, it associates candidates to feature vectors built by using terms occurring in their social content and ranks the candidates by using their distance from the centroid of seeds, returning the top candidates. Our method can run iteratively, using the results as new seeds. In this paper we address the following research questions: (1) How does the reconstructed domain knowledge evolve if the candidates of one extraction are recursively used as seeds (2) How does the reconstructed domain knowledge spread geographically (3) Can the method be used to inspect the past, present, and future of knowledge (4) Can the method be used to find emerging knowledge?. This work was presented at The Web Conference 2018, MSM workshop.

Iterative knowledge extraction from social networks. The Web Conference 2018

Iterative knowledge extraction from social networks. The Web Conference 2018

Iterative knowledge extraction from social networks. The Web Conference 2018

Marco Brambilla

Over one billion cars interact with each other on the road every day. Each driver has his own driving style, which could impact safety, fuel economy and road congestion. Knowledge about the driving style of the driver could be used to encourage ``better" driving behaviour through immediate feedback while driving, or by scaling auto insurance rates based on the aggressiveness of the driving style. In this work we report on our study of driving behaviour profiling based on unsupervised data mining methods. The main goal is to detect the different driving behaviours, and thus to cluster drivers with similar behaviour. This paves the way to new business models related to the driving sector, such as Pay-How-You-Drive insurance policies and car rentals. Driver behavioral characteristics are studied by collecting information from GPS sensors on the cars and by applying three different analysis approaches (DP-means, Hidden Markov Models, and Behavioural Topic Extraction) to the contextual scene detection problems on car trips, in order to detect different behaviour along each trip. Subsequently, drivers are clustered in similar profiles based on that and the results are compared with a human-defined groundtruth on drivers classification. The proposed framework is tested on a real dataset containing sampled car signals. While the different approaches show relevant differences in trip segment classification, the coherence of the final driver clustering results is surprisingly high.

Driving Style and Behavior Analysis based on Trip Segmentation over GPS Info...

Driving Style and Behavior Analysis based on Trip Segmentation over GPS Info...

Driving Style and Behavior Analysis based on Trip Segmentation over GPS Info...

Marco Brambilla

For centuries, science (in German "Wissenschaft") has aimed to create ("schaften") new knowledge ("Wissen") from the observation of physical phenomena, their modelling, and empirical validation. Recently, a new source of knowledge has emerged: not (only) the physical world any more, but the virtual world, namely the Web with its ever-growing stream of data materialized in the form of social network chattering, content produced on demand by crowds of people, messages exchanged among interlinked devices in the Internet of Things. The knowledge we may find there can be dispersed, informal, contradicting, unsubstantiated and ephemeral today, while already tomorrow it may be commonly accepted. The challenge is once again to capture and create knowledge that is new, has not been formalized yet in existing knowledge bases, and is buried inside a big, moving target (the live stream of online data). The myth is that existing tools (spanning fields like semantic web, machine learning, statistics, NLP, and so on) suffice to the objective. While this may still be far from true, some existing approaches are actually addressing the problem and provide preliminary insights into the possibilities that successful attempts may lead to. The talk explores the mixed realistic-utopian domain of knowledge extraction and reports on some tools and cases where digital and physical world have brought together for better understanding our society.

Myths and challenges in knowledge extraction and analysis from human-generate...

Myths and challenges in knowledge extraction and analysis from human-generate...

Myths and challenges in knowledge extraction and analysis from human-generate...

Marco Brambilla

Knowledge bases like DBpedia, Yago or Google's Knowledge Graph contain huge amounts of ontological knowledge harvested from (semi-)structured, curated data sources, such as relational databases or XML and HTML documents. Yet, the Web is full of knowledge that is not curated and/or structured and, hence, not easily indexed, for ex- ample social data. Most work so far in this context has been dedicated to the extraction of entities, i.e., people, things or concepts. This poster describes our work toward the extraction of relationships among entities. The objective is reconstructing a typed graph of entities and relationships to represent the knowledge contained in social data, without the need for a-priori domain knowledge. The experiments with real datasets show promising performance across a variety of domains. The key distinguishing feature of the work is its focus on highly unstructured social data (tweets and Facebook posts) without reliable grammar structures. Traditional relation extraction approaches supervised , semi-supervised or unsupervised, commonly assume the availability of grammatically correct language corpora.

Harvesting Knowledge from Social Networks: Extracting Typed Relationships amo...

Harvesting Knowledge from Social Networks: Extracting Typed Relationships amo...

Harvesting Knowledge from Social Networks: Extracting Typed Relationships amo...

Marco Brambilla

Internet of Things technologies and applications are evolving and continuously gaining traction in all fields and environments, including homes, cities, services, industry and commercial enterprises. However, still many problems need to be addressed. For instance, the IoT vision is mainly focused on the technological and infrastructure aspect, and on the management and analysis of the huge amount of generated data, while so far the development of front-end and user interfaces for IoT has not played a relevant role in research. On the contrary, user interfaces in the IoT ecosystem they can play a key role in the acceptance of solutions by final adopters. In this paper we present a model-driven approach to the design of IoT interfaces, by defining a specific visual design language and design patterns for IoT\ applications, and we show them at work. The language we propose is defined as an extension of the OMG standard language called IFML.

Model-driven Development of User Interfaces for IoT via Domain-specific Comp...

Model-driven Development of User Interfaces for IoT via Domain-specific Comp...

Model-driven Development of User Interfaces for IoT via Domain-specific Comp...

Marco Brambilla

Consumer-centered software applications nowadays are required to be available both as mobile and desktop versions. However, the app design is frequently made only for one of the two (i.e., mobile first or web first) while missing an appropriate design for the other (which, in turn, simply mimics the interaction of the first one). This results into poor quality of the interaction on one or the other platform. Current solutions would require different designs, to be realized through different design methods and tools, and that may require to double development and maintenance costs. In order to mitigate such an issue, this paper proposes a novel approach that supports the design of both web and mobile applications at once. Starting from a unique requirement and business specification, where web– and mobile–specific aspects are captured through tagging, we derive a platform independent design of the system specified in IFML. This model is subsequently refined and detailed for the two platforms, and used to automatically generate both the web and mobile versions. If more precise interactions are needed for the mobile part, a blending with MobML, a mobile-specific modeling language, is devised. Full traceability of the relations between artifacts is granted.

A Model-Based Method for Seamless Web and Mobile Experience. Splash 2016 conf.

A Model-Based Method for Seamless Web and Mobile Experience. Splash 2016 conf.

A Model-Based Method for Seamless Web and Mobile Experience. Splash 2016 conf.

Marco Brambilla

Big Data and Stream Data Analysis at Politecnico di Milano

Big Data and Stream Data Analysis at Politecnico di Milano

Big Data and Stream Data Analysis at Politecnico di Milano

Marco Brambilla

The Web Science course focuses on the study of large-scale socio-technical systems associated with the World Wide Web. It considers the relationship between people and technology, the ways that society and technology complement one another and the way they impact on broader society. These analyses are inherently associated with Big Data management issues. The course is organised in four parts. 1. Syntax In the first part, the course introduces the basis of content analysis. If focuses on the syntactic aspects, covering the fundamentals of natural language processing and text mining. It describes the structure and typical characteristics of the different web sources, spanning search results, social media contents, social network structures, Web APIs, and so on. It also provides an overview of the basic Web analysis techniques applied in Web search and Web recommendation. 2. Semantics In the second part, the course presents semantic technologies. These technologies are very important nowadays because they allow to treat the "variety" dimension of Big Data, i.e., they enable integration of multiple and diverse sources of information, which is typical on the modern Web platform. Covered topics include: - RDF - a flexible data model to represent heterogeneous data - OWL - a flexible ontological language to model heterogeneous data sources - SPARQL - a query language for RDF. It shows how to put all the pieces together in order to achieve interoperability among heterogeneous information sources 3. Time The third part covers the realm of temporal-dependent data. The topics covered here allow to treat the "velocity" dimension of Big Data. It shows the importance for many Big Data analysis scenarios to process data stream, coming for instance from Internet of Things (IoT) and Social Media sources; and it describes how to apply semantic and syntactic techniques in the context of time-dependent information. For instance, it shows how to extend RDF to model RDF streams, how to extend SPARQL to continuously process RDF streams and how to reason on those RDF Streams 4. Applications In the fourth part, the course focuses on specific application scenarios and presents the typical settings and problems where the presented techniques can be applied. This part discusses settings such as: big data analysis for smart cities; data analytics for brand monitoring (marketing) and event monitoring; data analysis for trend detection and user engagement; and so on.

Web Science. An introduction

Web Science. An introduction

Web Science. An introduction

Marco Brambilla

Massive data integration technologies have been recently used to produce very large ontologies. However, knowledge in the world continuously evolves, and ontologies are largely incomplete for what concerns low-frequency data, belonging to the so-called long tail. Socially produced content is an excellent source for discovering emerging knowledge: it is huge, and immediately reflects the relevant changes which hide emerging entities. Thus, we propose a method for discovering emerging entities by extracting them from social content. We start from a purely-syntactic method as a baseline, and we propose a semantics-based method based on entity recognition and DBpedia. The method associates candidate entities to feature vectors, built from social content by using co-occurrence, and then extracts the emerging entities by using feature similarity measures. Once instrumented by experts through very simple initialization, the method is capable of finding emerging entities and extracting their relevant relationships to given types; the method can be continuously or periodically iterated, using the already identified emerged knowledge as new starting point. We validate our method by applying it to a set of diverse domain-specific application scenarios, spanning fashion, literature, exhibitions and so on. We show the approach at work and we demonstrate its effectiveness on datasets with different characterization in terms of coverage, dynamics and size.

On the Quest for Changing Knowledge. Capturing emerging entities from social ...

On the Quest for Changing Knowledge. Capturing emerging entities from social ...

On the Quest for Changing Knowledge. Capturing emerging entities from social ...

Marco Brambilla

Mais de Marco Brambilla (20)

Thesis Topics and Proposals @ Polimi Data Science Lab - 2023 - prof. Brambill...

Thesis Topics and Proposals @ Polimi Data Science Lab - 2023 - prof. Brambill...

Thesis Topics and Proposals @ Polimi Data Science Lab - 2023 - prof. Brambill...

Hierarchical Transformers for User Semantic Similarity - ICWE 2023

Hierarchical Transformers for User Semantic Similarity - ICWE 2023

Hierarchical Transformers for User Semantic Similarity - ICWE 2023

Exploring the Bi-verse.A trip across the digital and physical ecospheres

Exploring the Bi-verse.A trip across the digital and physical ecospheres

Exploring the Bi-verse.A trip across the digital and physical ecospheres

Conversation graphs in Online Social Media

Conversation graphs in Online Social Media

Conversation graphs in Online Social Media

Trigger.eu: Cocteau game for policy making - introduction and demo

Trigger.eu: Cocteau game for policy making - introduction and demo

Trigger.eu: Cocteau game for policy making - introduction and demo

Generation of Realistic Navigation Paths for Web Site Testing using RNNs and ...

Generation of Realistic Navigation Paths for Web Site Testing using RNNs and ...

Generation of Realistic Navigation Paths for Web Site Testing using RNNs and ...

Analyzing rich club behavior in open source projects

Analyzing rich club behavior in open source projects

Analyzing rich club behavior in open source projects

Analysis of On-line Debate on Long-Running Political Phenomena.The Brexit C...

Analysis of On-line Debate on Long-Running Political Phenomena.The Brexit C...

Analysis of On-line Debate on Long-Running Political Phenomena.The Brexit C...

Community analysis using graph representation learning on social networks

Community analysis using graph representation learning on social networks

Community analysis using graph representation learning on social networks

Available Data Science M.Sc. Thesis Proposals

Available Data Science M.Sc. Thesis Proposals

Available Data Science M.Sc. Thesis Proposals

Data Cleaning for social media knowledge extraction

Data Cleaning for social media knowledge extraction

Data Cleaning for social media knowledge extraction

Iterative knowledge extraction from social networks. The Web Conference 2018

Iterative knowledge extraction from social networks. The Web Conference 2018

Iterative knowledge extraction from social networks. The Web Conference 2018

Driving Style and Behavior Analysis based on Trip Segmentation over GPS Info...

Driving Style and Behavior Analysis based on Trip Segmentation over GPS Info...

Driving Style and Behavior Analysis based on Trip Segmentation over GPS Info...

Myths and challenges in knowledge extraction and analysis from human-generate...

Myths and challenges in knowledge extraction and analysis from human-generate...

Myths and challenges in knowledge extraction and analysis from human-generate...

Harvesting Knowledge from Social Networks: Extracting Typed Relationships amo...

Harvesting Knowledge from Social Networks: Extracting Typed Relationships amo...

Harvesting Knowledge from Social Networks: Extracting Typed Relationships amo...

Model-driven Development of User Interfaces for IoT via Domain-specific Comp...

Model-driven Development of User Interfaces for IoT via Domain-specific Comp...

Model-driven Development of User Interfaces for IoT via Domain-specific Comp...

A Model-Based Method for Seamless Web and Mobile Experience. Splash 2016 conf.

A Model-Based Method for Seamless Web and Mobile Experience. Splash 2016 conf.

A Model-Based Method for Seamless Web and Mobile Experience. Splash 2016 conf.

Big Data and Stream Data Analysis at Politecnico di Milano

Big Data and Stream Data Analysis at Politecnico di Milano

Big Data and Stream Data Analysis at Politecnico di Milano

Web Science. An introduction

Web Science. An introduction

Web Science. An introduction

On the Quest for Changing Knowledge. Capturing emerging entities from social ...

On the Quest for Changing Knowledge. Capturing emerging entities from social ...

On the Quest for Changing Knowledge. Capturing emerging entities from social ...

Último

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

Passkeys: Developing APIs to enable passwordless authentication Cody Salas, Sr Developer Advocate | Solutions Architect - Yubico Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Architecting Cloud Native Applications

Architecting Cloud Native Applications

Architecting Cloud Native Applications

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

sudhanshuwaghmare1

Dubai, known for its towering skyscrapers, luxurious lifestyle, and relentless pursuit of innovation, often finds itself in the global spotlight. However, amidst the glitz and glamour, the emirate faces its own set of challenges, including the occasional threat of flooding. In recent years, Dubai has experienced sporadic but significant floods, disrupting normalcy and posing unique challenges to its infrastructure. Among the critical nodes in this bustling metropolis is the Dubai International Airport, a vital hub connecting the world. This article delves into the intersection of Dubai flood events and the resilience demonstrated by the Dubai International Airport in the face of such challenges.

Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf

Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf

Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Juan lago vázquez

Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows. We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases. This video focuses on the deployment of external web forms using Jotform for Bonterra Impact Management. This solution can be customized to your organization’s needs and deployed to support the common use cases below: - Intake and consent - Assessments - Surveys - Applications - Program registration Interested in deploying web form automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Jeffrey Haguewood

The value of a flexible API Management solution for Open Banking Steve Melan, Manager for IT Innovation and Architecture - State's and Saving's Bank of Luxembourg Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

The action of the next cyber saga takes place in the mystical lands of the Asia-Pacific region, where the main characters began their digital activities in the middle of 2021 and qualitatively strengthened it in 2022. Corporate espionage, document theft, audio recordings, and data leaks from messaging platforms were all a matter of one day for Dark Pink. Their geographical focus may have started in the Asia-Pacific region, but their ambitions knew no bounds, targeting a European government ministry in a bold move to expand their portfolio. Their victim profile was as diverse as a UN meeting, targeting military organizations, government agencies, and even a religious organization. Because discrimination is not a fashionable agenda. In the world of cybercrime, they serve as a reminder that sometimes the most serious threats come in the most unassuming packages with a pink bow.

Cyberprint. Dark Pink Apt Group [EN].pdf

Cyberprint. Dark Pink Apt Group [EN].pdf

Cyberprint. Dark Pink Apt Group [EN].pdf

Overkill Security

When you’re building (micro)services, you have lots of framework options. Spring Boot is no doubt a popular choice. But there’s more! Take Quarkus, a framework that’s considered the rising star for Kubernetes-native Java. It always depends on what's best for your situation, but how to choose the best solution if you're comparing 2 frameworks? Both Spring Boot and Quarkus have their positives and negatives. Let us compare the two by live coding a couple of common use cases in Spring Boot and Quarkus. After this talk, you’ll be ready to get started with Quarkus yourself, and know when to select Quarkus or Spring Boot.

Spring Boot vs Quarkus the ultimate battle - DevoxxUK

Spring Boot vs Quarkus the ultimate battle - DevoxxUK

Spring Boot vs Quarkus the ultimate battle - DevoxxUK

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Product Anonymous

💉💊+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHABI}}+971581248768 +971581248768 Mtp-Kit (500MG) Prices » Dubai [(+971581248768**)] Abortion Pills For Sale In Dubai, UAE, Mifepristone and Misoprostol Tablets Available In Dubai, UAE CONTACT DR.Maya Whatsapp +971581248768 We Have Abortion Pills / Cytotec Tablets /Mifegest Kit Available in Dubai, Sharjah, Abudhabi, Ajman, Alain, Fujairah, Ras Al Khaimah, Umm Al Quwain, UAE, Buy cytotec in Dubai +971581248768''''Abortion Pills near me DUBAI | ABU DHABI|UAE. Price of Misoprostol, Cytotec” +971581248768' Dr.DEEM ''BUY ABORTION PILLS MIFEGEST KIT, MISOPROTONE, CYTOTEC PILLS IN DUBAI, ABU DHABI,UAE'' Contact me now via What's App…… abortion Pills Cytotec also available Oman Qatar Doha Saudi Arabia Bahrain Above all, Cytotec Abortion Pills are Available In Dubai / UAE, you will be very happy to do abortion in Dubai we are providing cytotec 200mg abortion pill in Dubai, UAE. Medication abortion offers an alternative to Surgical Abortion for women in the early weeks of pregnancy. We only offer abortion pills from 1 week-6 Months. We then advise you to use surgery if its beyond 6 months. Our Abu Dhabi, Ajman, Al Ain, Dubai, Fujairah, Ras Al Khaimah (RAK), Sharjah, Umm Al Quwain (UAQ) United Arab Emirates Abortion Clinic provides the safest and most advanced techniques for providing non-surgical, medical and surgical abortion methods for early through late second trimester, including the Abortion By Pill Procedure (RU 486, Mifeprex, Mifepristone, early options French Abortion Pill), Tamoxifen, Methotrexate and Cytotec (Misoprostol). The Abu Dhabi, United Arab Emirates Abortion Clinic performs Same Day Abortion Procedure using medications that are taken on the first day of the office visit and will cause the abortion to occur generally within 4 to 6 hours (as early as 30 minutes) for patients who are 3 to 12 weeks pregnant. When Mifepristone and Misoprostol are used, 50% of patients complete in 4 to 6 hours; 75% to 80% in 12 hours; and 90% in 24 hours. We use a regimen that allows for completion without the need for surgery 99% of the time. All advanced second trimester and late term pregnancies at our Tampa clinic (17 to 24 weeks or greater) can be completed within 24 hours or less 99% of the time without the need surgery. The procedure is completed with minimal to no complications. Our Women's Health Center located in Abu Dhabi, United Arab Emirates, uses the latest medications for medical abortions (RU-486, Mifeprex, Mifegyne, Mifepristone, early options French abortion pill), Methotrexate and Cytotec (Misoprostol). The safety standards of our Abu Dhabi, United Arab Emirates Abortion Doctors remain unparalleled. They consistently maintain the lowest complication rates throughout the nation. Our Physicians and staff are always available to answer questions and care for women in one of the most difficult times in their lives. The decision to have an abortion at the Abortion Cl

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

Three things you will take away from the session: • How to run an effective tenant-to-tenant migration • Best practices for before, during, and after migration • Tips for using migration as a springboard to prepare for Copilot in Microsoft 365 Main ideas: Migration Overview: The presentation covers the current reality of cross-tenant migrations, the triggers, phases, best practices, and benefits of a successful tenant migration Considerations: When considering a migration, it is important to consider the migration scope, performance, customization, flexibility, user-friendly interface, automation, monitoring, support, training, scalability, data integrity, data security, cost, and licensing structure Next Wave: The next wave of change includes the launch of Copilot, which requires businesses to be prepared for upcoming changes related to Copilot and the cloud, and to consolidate data and tighten governance ShareGate: ShareGate can help with pre-migration analysis, configurable migration tool, and automated, end-user driven collaborative governance

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

AWS Community Day CPH - Three problems of Terraform

AWS Community Day CPH - Three problems of Terraform

AWS Community Day CPH - Three problems of Terraform

Andrey Devyatkin

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

Martijn de Jong

Último (20)

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Architecting Cloud Native Applications

Architecting Cloud Native Applications

Architecting Cloud Native Applications

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf

Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf

Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Cyberprint. Dark Pink Apt Group [EN].pdf

Cyberprint. Dark Pink Apt Group [EN].pdf

Cyberprint. Dark Pink Apt Group [EN].pdf

Spring Boot vs Quarkus the ultimate battle - DevoxxUK

Spring Boot vs Quarkus the ultimate battle - DevoxxUK

Spring Boot vs Quarkus the ultimate battle - DevoxxUK

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

AWS Community Day CPH - Three problems of Terraform

AWS Community Day CPH - Three problems of Terraform

AWS Community Day CPH - Three problems of Terraform

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

The WebML innovation cycle

1. WebML WebML 10 (or 15?) years, without showing it Marco Brambilla Politecnico di Milano marco.brambilla@polimi.itmarcobrambimarcobrambi

2.

3. The strategy

4.

5. The need Conceptual modeling Abstraction from the technology .. But NOT From the technological opportunities From the requirements Innovation Extensibility

6. The Strategy Virtuous innovation cycle

7. The Strategy Retrospective Virtuous Cycle At two levels: Macro-innovations Refinement of each innovation Repeatability of the experience.. Not granted!

8. innovation Research (Politecnico) Tool vendor (WebRatio) Toolsuite, industrial requirements Teaching (university courses) innovation toolsuite WebML Design method, language, and platform innovation Customers (requirement providers) requirements use cases Final customers (EU) Research Project consortia Software houses and integrators

9. The history “Amarcord”? (F. Fellini, 1973)

10. 1. AutoWeb Once upon a time ... 1998 W3I3 project The research starts

11. 2. WebML And then ... 1999 Teaching and consolidation at Politecnico

12. 3. WebML in action And then ... 2000 The first “customer”

13. 3. WebML in action And then ... 2000 The first “customer” No company or product yet Features implemented at night in Italy upon customers request in the US during the day 

14. 4. Web Services And then ... 2003 SOA, Services, Mashups First research solution:

15. 4. Web Services And then ... 2005 Refinement and implementation

16. 5. Business Processes And then ... 2004 Business processes andorchestrations Research proposal:

17. 5. Business Processes And then ... 2010 Industrial implementation and refinement Directly in the WebRatio tool After a few years (based on customers need)

18. 6. Semantic Web And then ... 2005

19. 6. Semantic Web Still a research project only But.. What about the future? Linked data, ...

20. 7. RIA - AJAX And then ... 2005 Rich Web interfaces Theoretical model in the research group And simplified model implemented in the tool immediately available Future: a new, comprehensive model coming up

21. 8. Social Web / BPM Today

22. 8. Social Web / BPM Oggi

23. 9. Standardization Today Strategic effort within OMG (Object Management Group)

24. 9. ... What about the future? Search, Interfaces, Modernization And...?

25. Conclusion Virtuous cycle