Data Analytics For Social Microblogging Platforms

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data. Investigates various methodologies and algorithms for data summarization, clustering and classification Covers both theory and practical applications from around the world, across all related disciplines of Intelligent Information Filtering and Organization Systems Explores different challenges and issues related to spam filtering, attribute selection, and classification for large datasets

This book constitutes the refereed proceedings of the 4th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2017, held in Gurgaon, India, in October 2017. The 66 revised full papers presented were carefully reviewed and selected from 329 submissions. The papers are organized in topical sections on big data analysis, data centric programming, next generation computing, social and web analytics, security in data science analytics.

A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.

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 presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2022), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India in January 2022. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This volume covers cutting-edge research in two prominent areas – computational intelligence and data analytics, and allied research areas.

This book constitutes revised papers from the six workshops held at the 19th International Conference on Business Information Systems, BIS 2016, held in Leipzig, Germany, in July 2016. The workshops included in this volume are: * The 8th Workshop on Applications of Knowledge-Based Technologies in Business - AKTB2016 accepted 7 papers from 14 submissions and features 1 invited talk. * The 7th Workshop on Business and IT Alignment - BITA 2016 selected 6 papers from 12 submissions. * The Workshop on Big Data and Business Analytics Ecosystems - DeBASE 2016 has 4 papers in this volume. * The First International Workshop on Intelligent Data Analysis in Integrated Social CRM - iCRM 2016 features 5 contributions. * The Second International Workshop on Digital Enterprise Engineering and Architecture - IDEA 2016 contributes 4 papers to this volume. * The First International Workshop on Integrative Analysis and Computation of Life Data for Smart Ecosystems - INCLuDE 2016 publishes 4 research papers. In addition, BIS hosted a Doctoral Consortium which was organized in a workshop formula. The best papers from this event are included in the book. In total, the workshops had 84 submissions of which 38 were accepted for publication.

This book constitutes the refereed conference proceedings of the Fourth International Conference on Big Data Analytics, BDA 2015, held in Hyderabad, India, in December 2015. The 9 revised full papers and 9 invited papers were carefully reviewed and selected from 61 submissions and cover topics on big data: security and privacy; big data in commerce; big data: models and algorithms; and big data in medicine.

This book constitutes the thoroughly refereed conference proceedings of the Second International Conference on Big Data Analytics, BDA 2013, held in Mysore, India, in December 2013. The 13 revised full papers were carefully reviewed and selected from 49 submissions and cover topics on mining social media data, perspectives on big data analysis, graph analysis, big data in practice.