Examine domain-specific research about works and the problems inherent in their storage and retrieval! This book addresses the issue of focusing on known-item identification and retrieval vs. collocation and retrieval of works in the construction of catalogs. Works as Entities for Information Retrieval reports significant research on the role of works as key entities for information retrieval, focusing on the importance of works in information-need and the importance of recognizing and using the work entity in the construction of bibliographic databases, Internet search engines, etc. This single source brings together librarians and scholars from around the world—the United States, Denmark, Canada, Australia, and India—to examine the most recent research on works and on systems to facilitate their retrieval. They share their expertise on essential aspects of works cataloging, including: record clustering for works of fiction ways to define and categorize video works conceptualizing the bibliographic record as text the semiotics of scientific works performed works and AACR2R ways to catalog scientific models cataloging digitized rare books and electronic texts cataloging cartographic materials as works—with three fascinating case studies and more! Works as Entities for Information Retrieval will bring you up to date on essential aspects of works-related cataloging, including analyzing networks of related works; canonicity and the rate of evolution of works; epistemology and taxonomy; user-stipulated interaction with catalog displays of works; searcher-defined attributes of bibliographic works; works in relation to digital resources; and domain-specific analyses of video, scientific, cartographic, performance, theological, and digital works. Make it a part of your professional collection today!

This open access book covers all facets of entity-oriented search—where “search” can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selected topics are discussed in-depth, the goal being to establish fundamental techniques and methods as a basis for future research and development. Additional topics are treated at a survey level only, containing numerous pointers to the relevant literature. A roadmap for future research, based on open issues and challenges identified along the way, rounds out the book. The book is divided into three main parts, sandwiched between introductory and concluding chapters. The first two chapters introduce readers to the basic concepts, provide an overview of entity-oriented search tasks, and present the various types and sources of data that will be used throughout the book. Part I deals with the core task of entity ranking: given a textual query, possibly enriched with additional elements or structural hints, return a ranked list of entities. This core task is examined in a number of different variants, using both structured and unstructured data collections, and numerous query formulations. In turn, Part II is devoted to the role of entities in bridging unstructured and structured data. Part III explores how entities can enable search engines to understand the concepts, meaning, and intent behind the query that the user enters into the search box, and how they can provide rich and focused responses (as opposed to merely a list of documents)—a process known as semantic search. The final chapter concludes the book by discussing the limitations of current approaches, and suggesting directions for future research. Researchers and graduate students are the primary target audience of this book. A general background in information retrieval is sufficient to follow the material, including an understanding of basic probability and statistics concepts as well as a basic knowledge of machine learning concepts and supervised learning algorithms.

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

With the increased use of technology in modern society, high volumes of multimedia information exists. It is important for businesses, organizations, and individuals to understand how to optimize this data and new methods are emerging for more efficient information management and retrieval. Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest academic material in the field of information and communication technologies and explores how complex information systems interact with and affect one another. Highlighting a range of topics such as knowledge discovery, semantic web, and information resources management, this multi-volume book is ideally designed for researchers, developers, managers, strategic planners, and advanced-level students.

This book constitutes the thoroughly refereed post-proceedings of the satellite events of the 9th International Conference on the Semantic Web, ESWC 2012, held in Heraklion, Crete, Greece, in May 2012. This volume contains 49 full papers and 13 short papers describing the posters and demonstrations. (SUGGESTION/ HELP needed).

One of the challenges brought on by the digital revolution of the recent decades is the mechanism by which information carried by texts can be extracted in order to access its contents. The processing of named entities remains a very active area of research, which plays a central role in natural language processing technologies and their applications. Named entity recognition, a tool used in information extraction tasks, focuses on recognizing small pieces of information in order to extract information on a larger scale. The authors use written text and examples in French and English to present the necessary elements for the readers to familiarize themselves with the main concepts related to named entities and to discover the problems associated with them, as well as the methods available in practice for solving these issues.

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This twenty-sixth issue is a special issue with selected papers from the First International KEYSTONE Conference 2015 (IKC 2015), part of the keystone COST Action IC1302.