Download or read book Using Data Mining for Facilitating User Contributions in the Social Semantic Web written by and published by . This book was released on 2011 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Using Data Mining for Facilitating User Contributions in the Social Semantic Web written by Maryam Ramezani and published by GRIN Verlag. This book was released on 2011-11 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doctoral Thesis / Dissertation from the year 2011 in the subject Computer Science - Internet, New Technologies, grade: 1,0, Karlsruhe Institute of Technology (KIT), language: English, abstract: Social Web applications have emerged as powerful applications for Internet users allowing them to freely contribute to the Web content, organize and share information, and utilize the collective knowledge of others for discovering new topics, resources and new friends. While social Web applications such as social tagging systems have many benefits, they also present several challenges due to their open and adaptive nature. The amount of user generated data can be extremely large and since there is not any controlled vocabulary or hierarchy, it can be very difficult for users to find the information that is of their interest. In addition, attackers may attempt to distort the system's adaptive behavior by inserting erroneous or misleading annotations, thus altering the way in which information is presented to legitimate users. This thesis utilizes data mining and machine learning techniques to address these problems. In particular, we design and develop recommender systems to aid the user in contributing to the Social Semantic Web. In addition, we study intelligent techniques to combat attacks against social tagging systems. In our work, we first propose a framework that maps domain properties to recommendation technologies. This framework provides a systematic approach to find the appropriate recommendation technology for addressing a given problem in a specific domain. Second, we improve existing graph-based approaches for personalized tag recommendation in folksonomies. Third, we develop machine learning algorithms for recommendation of semantic relations to support continuous ontology development in a social semanticWeb environment. Finally, we introduce a framework to analyze different types of potential attacks against social tagging systems and evaluate their impact on t
Download or read book Social Semantic Web Mining written by Tope Omitola and published by Springer Nature. This book was released on 2022-06-01 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the last three chapters, we describe how the combination of web intelligence and social semantic data can be used to derive knowledge from the Social Web, starting at the community level (macro), and then moving through group mining (meso) to user profile mining (micro).
Download or read book Redesigning Worldwide Connections written by Michele Bonazzi and published by Cambridge Scholars Publishing. This book was released on 2016-01-14 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the next twenty years, the convergence of robotics, informatics, nano-bio-technologies, genetics, information technologies, and cognitive sciences will have a significant impact on society. This convergence will lead to a revolution in the way that science, health, energy, resources, production, consumption and environment are conceptualised. However, these technologies will also pose new and specific challenges in terms of sustainability, ethics, and even expectations of the future. Indeed, today, the word “future” is often associated with pessimism and fear, much more than it was in the past. In order to face all these technological, ethical and cultural challenges, governments, industries and societies will need a robust cognitive framework, in order to grasp the complex dimensions of the technological convergence in progress, and must rapidly develop effective strategies to face the situations that will, unavoidably, take place. This book provides, through systemic and complexity theories, some of the theoretical tools necessary to tackle the opportunities and risks of the future.
Download or read book Exploiting Semantic Web Knowledge Graphs in Data Mining written by P. Ristoski and published by IOS Press. This book was released on 2019-06-28 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains. The book will be of interest to all those working in the field of data mining and KDD.
Download or read book Semantic Mining of Social Networks written by Jie Tang and published by Springer Nature. This book was released on 2022-06-01 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online social networks have already become a bridge connecting our physical daily life with the (web-based) information space. This connection produces a huge volume of data, not only about the information itself, but also about user behavior. The ubiquity of the social Web and the wealth of social data offer us unprecedented opportunities for studying the interaction patterns among users so as to understand the dynamic mechanisms underlying different networks, something that was previously difficult to explore due to the lack of available data. In this book, we present the architecture of the research for social network mining, from a microscopic point of view. We focus on investigating several key issues in social networks. Specifically, we begin with analytics of social interactions between users. The first kinds of questions we try to answer are: What are the fundamental factors that form the different categories of social ties? How have reciprocal relationships been developed from parasocial relationships? How do connected users further form groups? Another theme addressed in this book is the study of social influence. Social influence occurs when one's opinions, emotions, or behaviors are affected by others, intentionally or unintentionally. Considerable research has been conducted to verify the existence of social influence in various networks. However, few literature studies address how to quantify the strength of influence between users from different aspects. In Chapter 4 and in [138], we have studied how to model and predict user behaviors. One fundamental problem is distinguishing the effects of different social factors such as social influence, homophily, and individual's characteristics. We introduce a probabilistic model to address this problem. Finally, we use an academic social network, ArnetMiner, as an example to demonstrate how we apply the introduced technologies for mining real social networks. In this system, we try to mine knowledge from both the informative (publication) network and the social (collaboration) network, and to understand the interaction mechanisms between the two networks. The system has been in operation since 2006 and has already attracted millions of users from more than 220 countries/regions.
Download or read book Handbook of Research on Social Dimensions of Semantic Technologies and Web Services written by Cruz-Cunha, Maria Manuela and published by IGI Global. This book was released on 2009-05-31 with total page 1099 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book discusses the new technologies of semantic Web, transforming the way we use information and knowledge"--Provided by publisher.
Download or read book Mining the Social Web written by Matthew A. Russell and published by "O'Reilly Media, Inc.". This book was released on 2013-10-04 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit Take advantage of more than two-dozen Twitter recipes, presented in O’Reilly’s popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.
Download or read book Semantic Data Mining written by A. Ławrynowicz and published by IOS Press. This book was released on 2017-04-18 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.
Download or read book Sustaining Mobile Learning written by Wan Ng and published by Routledge. This book was released on 2015-07-16 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mobile technologies are one of the fastest growing areas of technology in education. For learners, they offer an appealing opportunity to transcend teacher-defined knowledge and approaches by being able to access multiple, alternative sources of information anytime and anywhere. While the pace of engagement with and research into the educational applications of mobile technologies has picked up dramatically in the last decade, there is no consolidated view of how to sustain the practices or opportunities that are being explored. Sustainability is a complex but crucial issue in mobile learning as educational institutions are usually required to make substantial investments in mobile devices and associated technologies, time and training to initiate mobile learning programs. The complexity of sustainable mobile learning programs is further exacerbated by the fast pace of change of digital technologies, where with every change, new possibilities are opened up and investments required. In addition, educators are still attempting to reconcile institutions of formal education with informal mobile learning. The book addresses these issues, with a particular focus on: exploring the challenges surrounding the sustainability of mobile learning in K-12 and higher education investigating the importance of sustaining mobile learning for diverse populations of students globally discussing theoretical models for the sustainability of mobile learning providing the reader with strategies for sustaining mobile learning. Presenting new research alongside theoretical models and ideas for practice, the book will appeal to researchers, academics, and postgraduate students in the fields of education and mobile learning, as well as those working in teacher education.
Download or read book Exploiting Semantic Web Knowledge Graphs in Data Mining written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Social Semantic Web Mining Big Data Analytics for Political Attitudes and Mentalities Research written by Markus Schatten and published by . This book was released on 2015 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book User Modeling Adaptation and Personalization written by Judith Masthoff and published by Springer. This book was released on 2012-06-19 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20 th International Conference on User Modeling, Adaptation, and Personalization, held in Montreal, Canada, in July 2012. The 22 long and 7 short papers of the Research Paper Track presented were carefully reviewed and selected from 101 submissions. The papers are organized in topical sections on user engagement; trust; user motivation, attention, and effort; recommender systems (including topics such as matrix factorization, critiquing, noise and spam in recommender systems); user centered design and evaluation; educational data mining; modeling learners; user models in microblogging; and visualization. The Industry Paper Track covered innovative commercial implementations or applications of UMAP technologies, and experience in applying recent research advances in practice. 2 long and 1 short papers were accepted of 5 submissions.
Download or read book Web Mining written by Bettina Berendt and published by . This book was released on 2014-01-15 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Domain Driven Data Mining written by Longbing Cao and published by Springer Science & Business Media. This book was released on 2010-01-08 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. It bridges the gap between business expectations and research output.
Download or read book Social Media Mining and Social Network Analysis Emerging Research written by Xu, Guandong and published by IGI Global. This book was released on 2013-01-31 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social Media Mining and Social Network Analysis: Emerging Research highlights the advancements made in social network analysis and social web mining and its influence in the fields of computer science, information systems, sociology, organization science discipline and much more. This collection of perspectives on developmental practice is useful for industrial practitioners as well as researchers and scholars.
Download or read book Handbook of Research on Methods and Techniques for Studying Virtual Communities Paradigms and Phenomena written by Daniel, Ben Kei and published by IGI Global. This book was released on 2010-11-30 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book satisfies the need for methodological consideration and tools for data collection, analysis and presentation in virtual communities, covering studies on various types of virtual communities, making this reference a comprehensive source of research for those in the social sciences and humanities"--Provided by publisher.
