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Abstract

Recent years have seen an explosive growth in the use of new database applications such as CAD/CAM systems, spatial information systems, and multimedia information systems. The needs of these applications are far more complex than traditional business applications. They call for support of objects with complex data types, such as images and spatial objects, and for support of objects with wildly varying numbers of index terms, such as documents. Traditional indexing techniques such as the B-tree and its variants do not efficiently support these applications, and so new indexing mechanisms have been developed.As a result of the demand for database support for new applications, there has been a proliferation of new indexing techniques. The need for a book addressing indexing problems in advanced applications is evident. For practitioners and database and application developers, this book explains best practice, guiding the selection of appropriate indexes for each application. For researchers, this book provides a foundation for the development of new and more robust indexes. For newcomers, this book is an overview of the wide range of advanced indexing techniques. "Indexing Techniques for Advanced Database Systems" is suitable as a secondary text for a graduate level course on indexing techniques, and as a reference for researchers and practitioners in industry.

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Abstract

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

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Abstract

Metadata research has emerged as a discipline cross-cutting many domains, focused on the provision of distributed descriptions (often called annotations) to Web resources or applications. Such associated descriptions are supposed to serve as a foundation for advanced services in many application areas, including search and location, personalization, federation of repositories and automated delivery of information. Indeed, the Semantic Web is in itself a concrete technological framework for ontology-based metadata. For example, Web-based social networking requires metadata describing people and their interrelations, and large databases with biological information use complex and detailed metadata schemas for more precise and informed search strategies. There is a wide diversity in the languages and idioms used for providing meta-descriptions, from simple structured text in metadata schemas to formal annotations using ontologies, and the technologies for storing, sharing and exploiting meta-descriptions are also diverse and evolve rapidly. In addition, there is a proliferation of schemas and standards related to metadata, resulting in a complex and moving technological landscape - hence, the need for specialized knowledge and skills in this area. The Handbook of Metadata, Semantics and Ontologies is intended as an authoritative reference for students, practitioners and researchers, serving as a roadmap for the variety of metadata schemas and ontologies available in a number of key domain areas, including culture, biology, education, healthcare, engineering and library science.

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Classification

004.67/8 22

DDC

004.67/8 22

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Abstract

This book constitutes the thoroughly refereed post-conference proceedings of the First COST Action IC1302 International KEYSTONE Conference on semantic Keyword-based Search on Structured Data Sources, IKC 2015, held in Coimbra, Portugal, in September 2015. The 13 revised full papers, 3 revised short papers, and 2 invited papers were carefully reviewed and selected from 22 initial submissions. The paper topics cover techniques for keyword search, semantic data management, social Web and social media, information retrieval, benchmarking for search on big data.

Date

1. 2.2016 18:25:22