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

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nexusstc/Entity-Oriented Search/5418b2b8f4d1c86611ec2c865708638c.pdf

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zlib/Business & Economics/Sales & Marketing/Krisztian Balog/Entity-Oriented Search_3661611.pdf

Balog, Krisztian

Springer International Publishing AG

Springer Nature Switzerland AG

Springer Open

The Information Retrieval Series, 1st ed. 2018, Cham, 2018

Information retrieval series, 39, Cham, Switzerland, 2018

The Information Retrieval Series 39, 1st ed., 2018

1st ed. 2018 edition, PT, 2018

Springer Nature, Cham, 2018

Switzerland, Switzerland

Oct 16, 2018

sm72227103

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Source title: Entity-Oriented Search (The Information Retrieval Series (39))

Open Access Unrestricted online access
Creative Commons https://creativecommons.org/licenses/by/4.0
English

Front Matter ....Pages i-xix
Introduction (Krisztian Balog)....Pages 1-23
Meet the Data (Krisztian Balog)....Pages 25-53
Front Matter ....Pages 55-55
Term-Based Models for Entity Ranking (Krisztian Balog)....Pages 57-99
Semantically Enriched Models for Entity Ranking (Krisztian Balog)....Pages 101-143
Front Matter ....Pages 145-145
Entity Linking (Krisztian Balog)....Pages 147-188
Populating Knowledge Bases (Krisztian Balog)....Pages 189-222
Front Matter ....Pages 223-223
Understanding Information Needs (Krisztian Balog)....Pages 225-267
Leveraging Entities in Document Retrieval (Krisztian Balog)....Pages 269-297
Utilizing Entities for an Enhanced Search Experience (Krisztian Balog)....Pages 299-336
Conclusions and Future Directions (Krisztian Balog)....Pages 337-348
Back Matter ....Pages 349-351

The Information Retrieval Series
Erscheinungsdatum: 16.10.2018

2018-10-08