Big Data and Stream Data Analysis at Politecnico di Milano

DevOps for Enterprise Systems

Latest Trends in Technology:BigData Analytics, Virtualization, Cloud Computi...

Abzetdin Adamov

IBM InterConnect 2013 Mobile Keynote: Marie Wieck

IBM Events

Trends on Information Technology

Carlos J. Costa

Latest trends in information technology

Eldos Kuriakose

Technical Comptency_ppt

Skillwise Consulting

IBM Z for the Digital Enterprise 2018 - Z Keynote

Bi marabia11 en

MobileIrn Presentation

Wing Venture Capital

Bi marabia9 en

Ethical AI: Establish an AI/ML Governance framework addressing Reproducibility, Explainability, Bias & Accountability for Enterprise AI use-cases. Presentation on “Open Source Enterprise AI/ML Governance” at Linux Foundation’s Open Compliance Summit, Dec 2020 (https://events.linuxfoundation.org/open-compliance-summit/) Full article: https://towardsdatascience.com/ethical-ai-its-implications-for-enterprise-ai-use-cases-and-governance-81602078f5db

Ethical AI - Open Compliance Summit 2020

Debmalya Biswas

20191126 modulair IFC

Léon Berlo

Bi marabia10 en

Ministry of Higher Education

Step by step AI Day 3: AI Technologies

Martin Polozadeh

Map Middle East 2009 - Enterprise Mashups in the Clouds

metalalp

Ecom

shilpa2757

Mais procurados (20)

Iit 1782 designing for the internet of things (io t) v4 gb

Icp 3273-the iiot understanding designing and developing the bigger picture v2

[GE207] Session03: Digital Technology Trends

Case Study Mm

Bimarabia3en

Latest Trends in Technology:BigData Analytics, Virtualization, Cloud Computi...

IBM InterConnect 2013 Mobile Keynote: Marie Wieck

Trends on Information Technology

Latest trends in information technology

Technical Comptency_ppt

IBM Z for the Digital Enterprise 2018 - Z Keynote

Bi marabia11 en

MobileIrn Presentation

Bi marabia9 en

Ethical AI - Open Compliance Summit 2020

20191126 modulair IFC

Bi marabia10 en

Step by step AI Day 3: AI Technologies

Map Middle East 2009 - Enterprise Mashups in the Clouds

Ecom

Destaque

Chapter 2.1 : Data Stream

Abstract: There’s no question that we are seeing an increase in the availability of streaming, time-series data. Largely driven by the rise of the Internet of Things (IoT) and connected real-time data sources, we now have an enormous number of applications with sensors that produce important data that changes over time. This data presents a challenge and opportunity for businesses across every industry. How do they handle the onslaught of streaming data? How can they exploit it to make decisions in real-time? One way is to detect, in real time, when something unusual occurs. Early anomaly detection in streaming data has significant implications, yet can be very difficult to execute. It requires detectors to process data in real-time, not batches, and learn while simultaneously making predictions. In this talk, we’ll look at algorithms designed for such data and analyze the components that lead to optimal performance. We’ll also discuss a new benchmark with a labeled, real-world data set, designed to provide a controlled and repeatable environment of open-source tools to test and measure anomaly detection algorithms on streaming data. How do we score in a way that rewards algorithms that detect all anomalies as soon as possible, triggers no false alarms, works with real-world time-series data across a variety of domains, and automatically adapts to changing statistics?

Detecting Anomalies in Streaming Data

Subutai Ahmad

Data streaming algorithms

Sandeep Joshi

[RakutenTechConf2013] [D-3_2] Counting Big Databy Streaming Algorithms

Rakuten Group, Inc.

Streaming Algorithms

Joe Kelley

Data Stream Outlier Detection Algorithm

Hamza Aslam

Stream processing using Apache Storm - Big Data Meetup Athens 2016

Adrianos Dadis

Streaming data presents new challenges for statistics and machine learning on extremely large data sets. Tools such as Apache Storm, a stream processing framework, can power range of data analytics but lack advanced statistical capabilities. These slides are from the Apache.con talk, which discussed developing streaming algorithms with the flexibility of both Storm and R, a statistical programming language. At the talk I dicsussed issues of why and how to use Storm and R to develop streaming algorithms; in particular I focused on: • Streaming algorithms • Online machine learning algorithms • Use cases showing how to process hundreds of millions of events a day in (near) real time See: https://apacheconna2015.sched.org/event/09f5a1cc372860b008bce09e15a034c4#.VUf7wxOUd5o

Data Stream Algorithms in Storm and R

Radek Maciaszek

Discover.hdp2.2.storm and kafka.final

Hortonworks

http://flink-forward.org/kb_sessions/streaming-ml-with-flink/ As continuous big data processing is gaining popularity it naturally implies that there is a need to transition many of the distributed machine learning functionality to a streaming backend. The most common use case is to give streaming predictions based on the model learnt in batch, however in some cases it is beneficial to also update the model on the fly. It is not uncommon that streaming learners need different algorithms than their batch counterparts. The talk discusses the common use cases and the pitfalls of the streaming ML transition through the example of recommender systems. It also offer a dive into the implementation of a Scala library augmenting FlinkML with streaming predictors.

Márton Balassi Streaming ML with Flink-

Flink Forward

Data Stream Analytics - Why they are important

Paris Carbone

Advanced data science algorithms applied to scalable stream processing by Dav...

Big Data Spain

Destaque (12)

Chapter 2.1 : Data Stream

Detecting Anomalies in Streaming Data

Data streaming algorithms

[RakutenTechConf2013] [D-3_2] Counting Big Databy Streaming Algorithms

Streaming Algorithms

Data Stream Outlier Detection Algorithm

Stream processing using Apache Storm - Big Data Meetup Athens 2016

Data Stream Algorithms in Storm and R

Discover.hdp2.2.storm and kafka.final

Márton Balassi Streaming ML with Flink-

Data Stream Analytics - Why they are important

Advanced data science algorithms applied to scalable stream processing by Dav...

Semelhante a Big Data and Stream Data Analysis at Politecnico di Milano

Big data session five ( a )f

marukanda

Datascience

Dr. Hemant Kumar Singh

Data science

Dr. Hemant Kumar Singh

THE INTERNET OF THINGS AND HOW TO CONNECT IT This presentation, delivered to the Denver Google Developer's Group on April 28 by Laurie Lamberth, has three parts. A. IoT Overview. What it is, how it's connected, how big is the market, how fast is it growing B. Not Your Father's Network. Overview of the new generation of machine-ceentric networks coming to market, why they are needed, what they look like and how they perform. Plus profiles of three new IOT networks (SIGFOX, LoRa, Weightless-N) C. Not Your Father's Platform. Overview of the new generation of platforms cfour oming to market that blur the previous "bright line" between device and application management platforms. Plus profiles of three new IOT platforms (machineshop.io, Xively, Kii, ThingWorx)

Self-Driving Cars, Smart Watches and Heads-Up Displays... Oh My!

Laurie Lamberth

Talk by Diego Oppenheimer CEO of Algorithmia.com at Data Day Texas 2016. Peter Sondergaard VP of Research for Gartner recently said the next digital gold rush is "How we do something with data not just what you do with it". During this talk we will cover a brief history of the different algorithmic advances in computer vision, natural language processing, machine learning and general AI and how they are being applied to Big Data today. From there we will talk about how algorithms are playing a crucial part in the next Big Data revolution, new opportunities that are opening up for startups and large companies alike as well as a first look into the role Algorithm Marketplaces will play in this space.

Algorithm Marketplace and the new "Algorithm Economy"

Diego Oppenheimer

Top Business Intelligence Trends for 2016 by Panorama Software

Panorama Software

This session looks at where we are today with data and analytics and what is needed to transition to the Artificially Intelligent Enterprise. How do you mobilise developers to exploit what data scientists and business analysts have built? How do you align it all with business strategy to maximise business outcomes? How do you combine BI, predictive and prescriptive analytics, automation and reinforcement learning to get maximum value across the enterprise? What is the blueprint for building the artificially intelligent enterprise? •Data and analytics – Where are we? •Why is the journey only half-way done? •2021 and beyond – The new era of AI usage and not just build •The requirement – event-driven, on-demand and automated analytics •Operationalising what you build – DataOps, MLOps and RPA •Mobilising the masses to integrate AI into processes – what needs to be done? •Business strategy alignment – the guiding light to AI utilisation for high reward •Agility step change – the shift to no-code integration of AI by citizen developers •Recording decisions, and analysing business impact •Reinforcement-learning – transitioning to continuous reward

Building the Artificially Intelligent Enterprise

Databricks

The newest buzzword after Big Data is AI. From Google search to Facebook messenger bots, AI is also everywhere. • Machine learning has gone mainstream. Organizations are trying to build competitive advantage with AI and Big Data. • But, what does it take to build Machine Learning applications? Beyond the unicorn data scientists and PhDs, how do you build on your big data architecture and apply Machine Learning to what you do? • This talk will discuss technical options to implement machine learning on big data architectures and how to move forward.

From Big Data to AI

Maloy Manna, PMP®

A Review of Big data for Social Policy Decision Making

Ridi Fe

SuanIct-Bigdata desktop-final

stelligence

Cubitic: Predictive Analytics

huguk

Get a glimpse into the key trends that will drive mobility over the next 12 months and begin to map a course for dealing with upcoming changes to the mobility landscape, including: • The rise of one-button BYOD as a solution to securing multiple device vendors • The enterprise emergence of HTML-5 for app flexibility and control • Cloud computing advances the pressure to increase innovation and workloads at lower costs

Moving mobility forward 10 mobile predictions

Troy C. Fulton

Kartikey tripathi

KARTIKEY TRIPATHI

Watch full webinar here: https://bit.ly/3x7xVuR Organizations worldwide are adopting a variety of the public cloud service providers (i.e. AWS, Google, Microsoft) and each have a portfolio of storage, compute, network, and security options. All of which create significant challenges in managing a hybrid and multi-cloud enterprise architecture. Even worse is the impact to the governance and integration of data from the clouds and physical infrastructure to support the broad array of analytics and operational requirements. Can one public cloud provider meet all your needs today and in the future? How do you manage across multiple public and private clouds you have today and where your data exists? And, how would you manage and operate your multi-cloud and on-premises systems to gain value from your data in any of them? The Chief Research Officer at Ventana Research, Mark Smith, will expound the challenges and path ahead for virtualization and integration of your data and the clouds, setting an architectural path for best success.

The Virtualization of Clouds - The New Enterprise Data Architecture Opportunity

Denodo

Sr. Jon Ander, Internet de las Cosas y Big Data: ¿hacia dónde va la Industria?

INACAP

Let's make money from big data!

B Spot

Beyond the Classroom consists of events, workshops and presentations meant to introduce Computer Science students to learning opportunities in addition to their regular classroom experiences. Beyond the Classroom events are free and open to all NHCC CSci students. This presentation is about Big Data, how it changes the traditional data landscape, how different companies are using it, and which skills are in demand.

Big data and your career final

Marina Kerbel

A beginner's guide to Big data

AnushkaGupta763558

SKILLWISE-BIGDATA ANALYSIS

Skillwise Consulting

Internet of Things (IoT)

milemadinah

Semelhante a Big Data and Stream Data Analysis at Politecnico di Milano (20)

Big data session five ( a )f

Datascience

Data science

Self-Driving Cars, Smart Watches and Heads-Up Displays... Oh My!

Algorithm Marketplace and the new "Algorithm Economy"

Top Business Intelligence Trends for 2016 by Panorama Software

Building the Artificially Intelligent Enterprise

From Big Data to AI

A Review of Big data for Social Policy Decision Making

SuanIct-Bigdata desktop-final

Cubitic: Predictive Analytics

Moving mobility forward 10 mobile predictions

Kartikey tripathi

The Virtualization of Clouds - The New Enterprise Data Architecture Opportunity

Sr. Jon Ander, Internet de las Cosas y Big Data: ¿hacia dónde va la Industria?

Let's make money from big data!

Big data and your career final

A beginner's guide to Big data

SKILLWISE-BIGDATA ANALYSIS

Internet of Things (IoT)

Mais de Marco Brambilla

M.Sc. Thesis Topics and Proposals @ Polimi Data Science Lab - 2024 - prof. Br...

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

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

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

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

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

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 ...

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

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

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

Available Data Science M.Sc. Thesis Proposals

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

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

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...

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...

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 relation- ships 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...

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.

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

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 ...

Cities are growing as melting pots of people with different culture, religion, and language. In this paper, through multilingual analysis of Twitter contents shared within a city, we analyze the prevalent language in the different neighborhoods of the city and we compare the results with census data, in order to highlight any parallelisms or discrepancies between the two data sources. We show that the officially identified neighborhoods are actually representing significantly different communities and that the use of the social media as a data source helps to detect those weak signals that are not captured from traditional data.

Studying Multicultural Diversity of Cities and Neighborhoods through Social M...

Cara Menggugurkan Kandungan 087776558899

Mais de Marco Brambilla (20)

M.Sc. Thesis Topics and Proposals @ Polimi Data Science Lab - 2024 - prof. Br...

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

Hierarchical Transformers for User Semantic Similarity - ICWE 2023

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

Conversation graphs in Online Social Media

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

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

Analyzing rich club behavior in open source projects

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

Community analysis using graph representation learning on social networks

Available Data Science M.Sc. Thesis Proposals

Data Cleaning for social media knowledge extraction

Iterative knowledge extraction from social networks. The Web Conference 2018

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

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

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

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

Web Science. An introduction

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

Studying Multicultural Diversity of Cities and Neighborhoods through Social M...

Último

JUAL PILL CYTOTEC PALOPO SULAWESI 087776558899 OBAT PENGGUGUR KANDUNGAN PALOP...

Capstone slidedeck for my capstone project part 2.pdf

eliklein8

Capstone slidedeck for my capstone final edition.pdf

eliklein8

Marketing Plan - Social Media. The Sparks Foundation

solidgbemi

Whatsapp Number Escorts Call girls 8617370543 Available 24x7 Sri Ganganagar Call Girls Service Offer Genuine VIP Model Escorts Call Girls in Your Budget. Sri Ganganagar Call Girls Service Provide Real Call Girls Number. Make Your Sexual Pleasure Memorable with Our Sri Ganganagar Call Girls at Affordable Price. Top VIP Escorts Call Girls, High Profile Independent Escorts Call Girls, Housewife Women Escorts Call Girl, College Girls Escorts Call Girls, Russian Escorts Call girls Service in Your Budget.

Sri Ganganagar Escorts 🥰 8617370543 Call Girls Offer VIP Hot Girls

Whatsapp Number Escorts Call girls 8617370543 Available 24x7 Kayamkulam Call Girls Service Offer Genuine VIP Model Escorts Call Girls in Your Budget. Kayamkulam Call Girls Service Provide Real Call Girls Number. Make Your Sexual Pleasure Memorable with Our Kayamkulam Call Girls at Affordable Price. Top VIP Escorts Call Girls, High Profile Independent Escorts Call Girls, Housewife Women Escorts Call Girl, College Girls Escorts Call Girls, Russian Escorts Call girls Service in Your Budget.

BVG BEACH CLEANING PROJECTS- ORISSA , ANDAMAN, PORT BLAIR

Neha Kajulkar

Kayamkulam Escorts 🥰 8617370543 Call Girls Offer VIP Hot Girls

Whatsapp Number Escorts Call girls 8617370543 Available 24x7 Jhunjhunu Call Girls Service Offer Genuine VIP Model Escorts Call Girls in Your Budget. Jhunjhunu Call Girls Service Provide Real Call Girls Number. Make Your Sexual Pleasure Memorable with Our Jhunjhunu Call Girls at Affordable Price. Top VIP Escorts Call Girls, High Profile Independent Escorts Call Girls, Housewife Women Escorts Call Girl, College Girls Escorts Call Girls, Russian Escorts Call girls Service in Your Budget.

SEO Expert in USA - 5 Ways to Improve Your Local Ranking - Macaw Digital.pdf

macawdigitalseo2023

Jhunjhunu Escorts 🥰 8617370543 Call Girls Offer VIP Hot Girls

PEMESANAN OBAT ASLI : 087-776-558-899 Cara Menggugurkan Kandungan usia 1 2 3 4 5 6 7 8 bulan SEMARANG || obat penggugur kandungan SEMARANG || cara aborsi kandungan SEMARANG || obat penggugur kandungan 1 2 3 4 5 6 7 8 bulan SEMARANG || bagaimana cara menggugurkan kandungan SEMARANG || tips Cara aborsi kandungan SEMARANG || trik Cara menggugurkan janin SEMARANG || tata cara aman bagi ibu menyusui menggugurkan kandungan SEMARANG || klinik apotek jual obat penggugur kandungan SEMARANG || jamu PENGGUGUR KANDUNGAN SEMARANG || WAJIB TAU CARA ABORSI JANIN SEMARANG || GUGURKAN KANDUNGAN AMAN TANPA KURET SEMARANG || CARA Menggugurkan Kandungan tanpa efek samping SEMARANG || rekomendasi dokter obat herbal penggugur kandungan SEMARANG || ABORSI janin SEMARANG || aborsi kandungan SEMARANG || jamu herbal Penggugur kandungan SEMARANG || cara Menggugurkan Kandungan yang cacat SEMARANG || tata cara Menggugurkan Kandungan SEMARANG || obat penggugur kandungan di apotik kimia Farma SEMARANG || obat telat datang bulan SEMARANG || obat penggugur kandungan tuntas SEMARANG || obat penggugur kandungan alami SEMARANG || klinik aborsi janin gugurkan kandungan SEMARANG || Cytotec® misoprostol BPOM SEMARANG || OBAT PENGGUGUR KANDUNGAN CYTOTEC© SEMARANG || aborsi janin dengan pil Cytotec© SEMARANG || Cytotec© misoprostol BPOM 100% SEMARANG || penjual obat penggugur kandungan asli SEMARANG || klinik jual obat aborsi janin SEMARANG || obat penggugur kandungan di klinik k-24 SEMARANG || obat penggugur Cytotec© di apotek umum SEMARANG || CYTOTEC© ASLI SEMARANG || obat Cytotec© yang asli 200mcg SEMARANG || obat penggugur ASLI SEMARANG || pil Cytotec© tablet SEMARANG || cara gugurin kandungan SEMARANG || jual Cytotec© 200mg SEMARANG || dokter gugurkan kandungan SEMARANG || cara menggugurkan kandungan dengan cepat selesai dalam 24 jam secara alami buah buahan || usia kandungan 1 2 3 4 5 6 7 8 bulan masih bisa di gugurkan || obat penggugur kandungan cytotec dan gastrul SEMARANG || cara gugurkan pembuahan secara alami dan cepat SEMARANG || cara Menggugurkan janin di luar nikah SEMARANG || contoh aborsi janin SEMARANG || contoh obat penggugur kandungan asli SEMARANG || contoh cara Menggugurkan Kandungan yang benar SEMARANG || telat haid Bali || obat telat haid SEMARANG || obat telat menstruasi SEMARANG || cara Menggugurkan janin anak haram SEMARANG || cara aborsi menggugurkan janin yang tidak berkembang SEMARANG || gugurkan kandungan dengan obat Cytotec© SEMARANG || obat penggugur kandungan Cytotec 100% original SEMARANG || harga obat penggugur kandungan SEMARANG || obat peluntur janin SEMARANG || Obat peluntur kehamilan SEMARANG _____________________________________________ Cara Menggugurkan Kandungan Usia Janin 1 | 7 | 8 Bulan Dengan Cepat Dalam Hitungan Jam Secara Alami, Kami Siap Meneriman Pesanan Ke Seluruh Indonesia, Melputi: Ambon, Banda Aceh, Bandung, Banjarbaru, Batam, Bau-Bau, Bengkulu, Binjai, Blitar, Bontang, Cilegon, Cirebon, Depok, Gorontalo, Jakarta,

💊💊 OBAT PENGGUGUR KANDUNGAN SEMARANG 087776-558899 ABORSI KLINIK SEMARANG

Cara Menggugurkan Kandungan 087776558899

+971565801893 Mtp-Kit (500MG) Prices » Dubai [(+971565801893**)] Abortion Pills For Sale In Dubai, UAE, Mifepristone and Misoprostol Tablets Available In Dubai, UAE CONTACT DR.Leen Whatsapp +971565801893 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 +971565801893''''Abortion Pills near me DUBAI | ABU DHABI|UAE. Price of Misoprostol, Cytotec” +971565801893' 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 Clinic in Abu Dhabi, United Arab Emirates, (+971565801893)

+971565801893>> ORIGINAL CYTOTEC ABORTION PILLS FOR SALE IN DUBAI AND ABUDHABI<<

Health

Content strategy : Content empire and cash in

Kreators Lisbon

Call Girls in Delhi GTB Nagar Escort Service WhatsApp Call 9634446618 Girls in Call/ Us) (Delhi) We are providing high class, genuine call girls. Our escort service is affordable. Our Female Escorts Are Fun, Sexy, And Would Love The Chance To Have Your Company. We Are One Of The Oldest Escorts and Call Girls Agencies In Delhi. For both in-call and out-call calls, we have a great selection of ladies available at Callo Girls. All our Escorts Not Only Have Beautiful Faces, But They Have Great Personalities, Making Them The Perfect Companion For Any Occasion. You can come to our Delhi location which is very clean and hygienic, and is safe and secure. We also provide door-to-door services in Delhi, GTB Nagar . Out-Call: - You must come and pick up the girl from my place. In Delhi NCR, We Are Providing : - all types of girls Indian, North East, Foreigners, Air hostesses, and many More. For Details, Call/WhatsApp, 9634446618. In-call Shot 1500, 2,000 - In-call Night / Out-call Night 6,000, to 7,000 - Hi-Fi Rates Shot 9,000 to 10,000 Full Night 8,000 to 10,000 More Details, Call/WhatsApp, 9634446618. Russian Girls also available in Delhi NCR. Russian Girls :- 1 Hr Shot 10,000, 2,000 - Russian Girls :- 2 Hr Shot 12,000, 2,500 - Russian Girls :- 3 Hr Shot 15,000, 3,500 - Russian Girls :- 4 Hr Shot 18,000, 5,000.

Meet Incall & Out Escort Service in D -9634446618 | #escort Service in GTB Na...

Heena Escort Service

Whatsapp Number Escorts Call girls 8617370543 Available 24x7 Coorg Call Girls Service Offer Genuine VIP Model Escorts Call Girls in Your Budget. Coorg Call Girls Service Provide Real Call Girls Number. Make Your Sexual Pleasure Memorable with Our Coorg Call Girls at Affordable Price. Top VIP Escorts Call Girls, High Profile Independent Escorts Call Girls, Housewife Women Escorts Call Girl, College Girls Escorts Call Girls, Russian Escorts Call girls Service in Your Budget.

Coorg Escorts 🥰 8617370543 Call Girls Offer VIP Hot Girls

Klinik_ Apotek Onlin 085657271886 Solusi Menggugurkan Masalah Kehamilan Anda Jual Obat Aborsi Asli KLINIK ABORSI TERPEECAYA _ Jual Obat Aborsi Cytotec Misoprostol Asli 100% Ampuh Hanya 3 Jam Langsung Gugur || OBAT PENGGUGUR KANDUNGAN AMPUH MANJUR OBAT ABORSI OLINE" APOTIK Jual Obat Cytotec, Gastrul, Gynecoside Asli Ampuh. JUAL ” Obat Aborsi Tuntas | Obat Aborsi Manjur | Obat Aborsi Ampuh | Obat Penggugur Janin | Obat Pencegah Kehamilan | Obat Pelancar Haid | Obat terlambat Bulan | Ciri Obat Aborsi Asli | Obat Telat Bulan | Pil Aborsi Asli | Cara Menggugurkan Konten | Cara Aborsi Tuntas | Harga Obat Aborsi Asli | Pil Aborsi | Jual Obat Aborsi Cytotec | Cara Aborsi Sendiri | Cara Aborsi Usia 1 Bulan | Cara Aborsi Usia 2 Tahun | Cara Aborsi Usia 3 Bulan | Obat Aborsi Usia 4 Bulan | Cara Abrasi Usia 5 Bulan | Cara Menggugurkan Konten | Kandungan Obat Penggugur | Cara Menghitung Usia Konten | Cara Mengatasi Terlambat Bulan | Penjual Obat Aborsi Asli | Obat Aborsi Garansi | Kandungan Obat Peluntur | Obat Telat Datang Bulan | Obat Telat Haid | Obat Aborsi Paling Murah | Klinik Jual Obat Aborsi | Jual Pil Cytotec | Apotik Jual Obat Aborsi | Kandungan Dokter Abrasi | Cara Aborsi Cepat | Jual Obat Aborsi Bergaransi | Jual Obat Cytotec Asli | Obat Aborsi Aman Manjur | Obat Misoprostol Cytotec Asli. "APA ITU ABORSI" “Aborsi Adalah dengan membendung hormon yang di perlukan untuk mempertahankan kehamilan yaitu hormon progesteron, karena hormon ini dibendung, maka jalur kehamilan mulai membuka dan leher rahim menjadi melunak,sehingga mengeluarkan darah yang merupakan tanda bahwa obat telah bekerja || maksimal 1 jam obat diminum || PENJELASAN OBAT ABORSI USIA 1 _7 BULAN Pada usia kandungan ini, pasien akan merasakan sakit yang sedikit tidak berlebihan || sekitar 1 jam ||. namun hanya akan terjadi pada saatdarah keluar merupakan pertanda menstruasi. Hal ini dikarenakan pada usiakandungan 3 bulan,janin sudah terbentuk sebesar kepalan tangan orang dewasa. Cara kerja obat aborsi : JUAL OBAT ABORSI AMPUH dosis 3 bulan secara umum sama dengan cara kerja || DOSIS OBAT ABORSI 2 bulan”, hanya berbedanya selain mengisolasijanin juga menghancurkan janin dengan formula methotrexate dikandungdidalamnya. Formula methotrexate ini sangat ampuh untuk menghancurkan janinmenjadi serpihan-serpihan kecil akan sangat berguna pada saat dikeluarkan nanti. APA ALASAN WANITA MELAKUKAN ABORSI? Aborsi di lakukan wanita hamil baik yang sudah menikah maupun belum menikah dengan berbagai alasan , akan tetapi alasan yang utama adalah alasan-alasan non medis (termasuk aborsi sendiri / di sengaja/ buatan] MELAYANI PEMESANAN OBAT ABORSI SETIAP HARI, SIAP KIRIM KESELURUH KOTA BESAR DI INDONESIA DAN LUAR NEGERI. HUBUNGI PEMESANAN LEBIH NYAMAN VIA WA/: 085657271886

Jual Obat Aborsi Palu ( Taiwan No.1 ) 085657271886 Obat Penggugur Kandungan C...

ZurliaSoop

Capstone slide deck on the TikTok revolution

eliklein8

The Butterfly Effect

Thurston K. Atlas

Enhancing Consumer Trust Through Strategic Content Marketing

Digital Marketing Lab

Whatsapp Number Escorts Call girls 8617370543 Available 24x7 Madikeri Call Girls Service Offer Genuine VIP Model Escorts Call Girls in Your Budget. Madikeri Call Girls Service Provide Real Call Girls Number. Make Your Sexual Pleasure Memorable with Our Madikeri Call Girls at Affordable Price. Top VIP Escorts Call Girls, High Profile Independent Escorts Call Girls, Housewife Women Escorts Call Girl, College Girls Escorts Call Girls, Russian Escorts Call girls Service in Your Budget.

Madikeri Escorts 🥰 8617370543 Call Girls Offer VIP Hot Girls