This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

New In This Edition: This second edition of the Encyclopedia of GIS includes 30% to 50% new content. It provides up-to-date information on emerging topics such as spatial big data, smart-phone GIS, urban computing and mobile recommender systems. It also expands the first edition's rich set of GIS-related commercial and societal applications such as geo-targeting, geo-fencing and understanding climate changes, while enabling more comprehensive coverage of classical GIS topics such as map projections, global positioning systems and spatial cognition. The entries explain the key software, data sets and processes used by geographers and computational scientists. Additionally, the reference emphasizes the role of GIS in business and mobile intelligence. By offering more diversified GIS-related topics from theory and research than most of the other available literature, the authors equip newcomers to the field with principles as well as applications. With an accessible breadth of content and intuitive A-Z organization, this new edition of the encyclopedia is an invaluable reference for newcomers to the field of GIS, as well as researchers, students, developers and professionals who are interested in exploring this new dynamic area. Praise For The First Edition: "The focus here, however, is on the mathematical and computational aspects of GIS ... . This is very welcome to those practitioners who have been less exposed to some of the mathematical and computational aspects of GIS. This is also very welcome to the researcher or graduate student within any of the interdisciplinary areas that use GIS. ... I highly recommend it." (Pascal V. Calarco, ACM Computing Reviews, November, 2008) "This single-volume reference work is a highly welcome ... addition to the rapidly advancing field of geographic information systems. Peer-reviewed entries from over 300 contributors cover 41 topical subfields, with an overall emphasis on computational aspects of GIS. The volume is adequately illustrated with 723 figures and 90 tables in black and white. A full bibliography and concise list of entry terms are provided at the back of the work. ... Summing Up: Highly recommended. Upper-division geography students through professionals." (C. E. Smith, CHOICE, Vol. 45 (11), 2008) "The encyclopedia is divided into 41 fields, each one an important sub-area within GIS. ... the editors' organization of the material and comprehensive and systematic approach are superb and shall give students, eager readers as well as researchers an understanding of the topics in quite full depth and breadth. ... is lavishly illustrated with figures, graphs and tables, the design and execution of which are as perfect as the material they illustrate. ... it is sturdy and opens out nicely for study and reference." (Current Engineering Practice, 2008).

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

This book constitutes the refereed proceedings of the 14th International Conference on Web-Age Information Management, WAIM 2013, held in Beidaihe, China, in June 2013. The 47 revised full papers presented together with 29 short papers and 5 keynotes were carefully reviewed and selected from a total of 248 submissions. The papers are organized in topical sections on data mining; information integration and heterogeneous systems; big data; spatial and temporal databases; information extraction; new hardware and miscellaneous; query processing and optimization; social network and graphs; information retrieval; workflow systems and service computing; recommender systems; security, privacy, and trust; semantic Web and ontology.

Clustering is an important technique for discovering relatively dense sub-regions or sub-spaces of a multi-dimension data distribution. Clus tering has been used in information retrieval for many different purposes, such as query expansion, document grouping, document indexing, and visualization of search results. In this book, we address issues of cluster ing algorithms, evaluation methodologies, applications, and architectures for information retrieval. The first two chapters discuss clustering algorithms. The chapter from Baeza-Yates et al. describes a clustering method for a general metric space which is a common model of data relevant to information retrieval. The chapter by Guha, Rastogi, and Shim presents a survey as well as detailed discussion of two clustering algorithms: CURE and ROCK for numeric data and categorical data respectively. Evaluation methodologies are addressed in the next two chapters. Ertoz et al. demonstrate the use of text retrieval benchmarks, such as TRECS, to evaluate clustering algorithms. He et al. provide objective measures of clustering quality in their chapter. Applications of clustering methods to information retrieval is ad dressed in the next four chapters. Chu et al. and Noel et al. explore feature selection using word stems, phrases, and link associations for document clustering and indexing. Wen et al. and Sung et al. discuss applications of clustering to user queries and data cleansing. Finally, we consider the problem of designing architectures for infor mation retrieval. Crichton, Hughes, and Kelly elaborate on the devel opment of a scientific data system architecture for information retrieval."

This book constitutes the proceedings of the 5th International Conference on Knowledge Science, Engineering and Management, KSEM 2011, held in Irvine, CA, USA, in December 2011. The 34 revised full papers presented together with 7 short papers were carefully reviewed and selected from numerous submissions.

Clustering is an important technique for discovering relatively dense sub-regions or sub-spaces of a multi-dimension data distribution. Clus tering has been used in information retrieval for many different purposes, such as query expansion, document grouping, document indexing, and visualization of search results. In this book, we address issues of cluster ing algorithms, evaluation methodologies, applications, and architectures for information retrieval. The first two chapters discuss clustering algorithms. The chapter from Baeza-Yates et al. describes a clustering method for a general metric space which is a common model of data relevant to information retrieval. The chapter by Guha, Rastogi, and Shim presents a survey as well as detailed discussion of two clustering algorithms: CURE and ROCK for numeric data and categorical data respectively. Evaluation methodologies are addressed in the next two chapters. Ertoz et al. demonstrate the use of text retrieval benchmarks, such as TRECS, to evaluate clustering algorithms. He et al. provide objective measures of clustering quality in their chapter. Applications of clustering methods to information retrieval is ad dressed in the next four chapters. Chu et al. and Noel et al. explore feature selection using word stems, phrases, and link associations for document clustering and indexing. Wen et al. and Sung et al. discuss applications of clustering to user queries and data cleansing. Finally, we consider the problem of designing architectures for infor mation retrieval. Crichton, Hughes, and Kelly elaborate on the devel opment of a scientific data system architecture for information retrieval."

This two volume set LNCS 9642 and LNCS 9643 constitutes the refereed proceedings of the 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016, held in Dallas, TX, USA, in April 2016. The 61 full papers presented were carefully reviewed and selected from a total of 183 submissions. The papers cover the following topics: crowdsourcing, data quality, entity identification, data mining and machine learning, recommendation, semantics computing and knowledge base, textual data, social networks, complex queries, similarity computing, graph databases, and miscellaneous, advanced applications.

This two volume set LNCS 9642 and LNCS 9643 constitutes the refereed proceedings of the 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016, held in Dallas, TX, USA, in April 2016. The 61 full papers presented were carefully reviewed and selected from a total of 183 submissions. The papers cover the following topics: crowdsourcing, data quality, entity identification, data mining and machine learning, recommendation, semantics computing and knowledge base, textual data, social networks, complex queries, similarity computing, graph databases, and miscellaneous, advanced applications.

This book constitutes the proceedings of the First International Conference on Big Data Computing and Communications, BigCom 2015, held in Taiyuan, China, in August 2015. The 41 papers presented in this volume were carefully reviewed and selected from 74 submissions. They were organized in topical sections named: wireless communication and networks; database and big data; smart phone and sensing application; security and privacy; architecture and applications; sensor networks and RFID; social networks and recommendation; signal processing and pattern recognition; and routing and resource management.