The book studies the existing and potential connections between Social Network Analysis (SNA) and Formal Concept Analysis (FCA) by showing how standard SNA techniques, usually based on graph theory, can be supplemented by FCA methods, which rely on lattice theory. The book presents contributions to the following areas: acquisition of terminological knowledge from social networks, knowledge communities, individuality computation, other types of FCA-based analysis of bipartite graphs (two-mode networks), multimodal clustering, community detection and description in one-mode and multi-mode networks, adaptation of the dual-projection approach to weighted bipartite graphs, extensions to the Kleinberg's HITS algorithm as well as attributed graph analysis.
This book constitutes the refereed proceedings of the 7th International Conference on Formal Concept Analysis, ICFCA 2009, held in Darmstadt, Germany, in May 2009. The 15 revised full papers presented were carefully reviewed and selected from 29 submissions for inclusion in the book. The papers comprise state of the art research and present new results in Formal Concept Analysis and related fields. These results range from theoretical novelties to advances in FCA-related algorithmic issues, as well as application domains of FCA such as data visualization, information retrieval, machine learning, data analysis and knowledge management.
FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining. Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge. This edited book examines a set of important and relevant research directions in complex data management, and updates the contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts. For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.
The book studies the existing and potential connections between Social Network Analysis (SNA) and Formal Concept Analysis (FCA) by showing how standard SNA techniques, usually based on graph theory, can be supplemented by FCA methods, which rely on lattice theory. The book presents contributions to the following areas: acquisition of terminological knowledge from social networks, knowledge communities, individuality computation, other types of FCA-based analysis of bipartite graphs (two-mode networks), multimodal clustering, community detection and description in one-mode and multi-mode networks, adaptation of the dual-projection approach to weighted bipartite graphs, extensions to the Kleinberg's HITS algorithm as well as attributed graph analysis.
Presented in a comprehensive manner, this book provides a comprehensive foundation in algebraic approaches for the analysis of different types of social networks such as multiple, signed, and affiliation networks. The study of such configurations corresponds to the structural analysis within the social sciences, and the methods applied for the analysis are in the areas of abstract algebra, combinatorics, and graph theory. Current research in social networks has moved toward the examination of more realistic but also more complex social relations by which agents or actors are connected in multiple ways. Addressing this trend, this book offers hands-on training of the algebraic procedures presented along with the computer package multiplex, written by the book’s author specifically to perform analyses of multiple social networks. An introductory section on both complex networks and for R will feature, however the subjects themselves correspond to advanced courses on social network analysis with the specialization on algebraic models and methods.
Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems. Topics and Features: Provides an overview social network tools, and explores methods for discovering key players in social networks, designing self-organizing search systems, and clustering blog sites, surveys techniques for exploratory analysis and text mining of social networks, approaches to tracking online community interaction, and examines how the topological features of a system affects the flow of information, reviews the models of network evolution, covering scientific co-citation networks, nature-inspired frameworks, latent social networks in e-Learning systems, and compound communities, examines the relationship between the intent of web pages, their architecture and the communities who take part in their usage and creation, discusses team selection based on members’ social context, presents social network applications, including music recommendation and face recognition in photographs, explores the use of social networks in web services that focus on the discovery stage in the life cycle of these web services. This useful and comprehensive volume will be indispensible to senior undergraduate and postgraduate students taking courses in Social Intelligence, as well as to researchers, developers, and postgraduates interested in intelligent-social-networks research and related areas.
FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining. Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge. This edited book examines a set of important and relevant research directions in complex data management, and updates the contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts. For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.
This book constitutes extended and revised papers from the 19th International Conference on Enterprise Information Systems, ICEIS 2017, held in Porto, Portugal, in April 2017. The 28 papers presented in this volume were carefully reviewed and selected for inclusion in this book from a total of 318 submissions. They were organized in topical sections named: databases and information systems integration; artificial intelligence and decision support systems; information systems analysis and specification; software agents and internet computing; human-computer interaction; and enterprise architecture.
Zusammenfassung: This book constitutes the refereed proceedings of the 11th International Conference on Recent Trends in Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023. The 19 full papers 2 short papers and 1 demo paper included in this book were carefully reviewed and selected from 52 submissions. They were organized in topical sections as follows: Natural Language Processing; Computer Vision; Data Analysis and Machine Learning; Network Analysis; Theoretical Machine Learning and Optimization; and Demo Paper
This volume contains selected papers presented at ICFCA 2010, the 8th Int- national Conference on Formal Concept Analysis. The ICFCA conference series aims to be the prime forum for dissemination of advances in applied lattice and order theory, and in particular advances in theory and applications of Formal Concept Analysis. Formal Concept Analysis (FCA) is a ?eld of applied mathematics with its mathematical root in order theory, in particular the theory of complete lattices. Researchershadlongbeenawareofthefactthatthese?eldshavemanypotential applications.FCAemergedinthe1980sfrome?ortstorestructurelattice theory to promote better communication between lattice theorists and potential users of lattice theory. The key theme was the mathematical formalization of c- cept and conceptual hierarchy. Since then, the ?eld has developed into a growing research area in its own right with a thriving theoretical community and an - creasingnumberofapplicationsindataandknowledgeprocessingincludingdata visualization, information retrieval, machine learning, sofware engineering, data analysis, data mining in Web 2.0, analysis of social networks, concept graphs, contextual logic and description logics. ICFCA 2010 took place during March 15–18, 2010 in Agadir, Morocco. We received 37 high-quality submissions out of which 17 were chosen as regular papers in these proceedings after a competitive selection process. Less mature works that were still considered valuable for discussion at the conference were collected in the supplementary proceedings. The papers in the present volume coveradvancesinvariousaspectsofFCArangingfromitstheoreticalfoundations to its applications in numerous other ?elds. In addition to the regular papers, thisvolumealsocontainsfourkeynotepapersarisingfromtheseveninvitedtalks given at the conference. We are also delighted to include a reprint of Bernhard Ganter’sseminalpaper on hiswell-knownalgorithmfor enumerating closedsets.
