Overview
- Presents techniques of query understanding and reformulation for search engines, including query classification, query tagging, query suggestion, query auto completion, and spelling correction
- Provides extensive experimental results on various query log data sets to demonstrate the performance of various algorithms as well as guidelines for practical use
- Written mainly for researchers and graduate students specializing in information retrieval or web-based systems
Part of the book series: The Information Retrieval Series (INRE, volume 46)
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About this book
Query understanding is a fundamental part of search engines. It is responsible to precisely infer the intent of the query formulated by the search user, to correct spelling errors in his/her query, to reformulate the query to capture its intent more accurately, and to guide the user in formulating a query with precise intent.
The book will be invaluable to researchers and graduate students in computer or information science and specializing in information retrieval or web-based systems, as well as to researchers and programmers working on the development or improvement of products related to search engines.
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Keywords
Table of contents (9 chapters)
Editors and Affiliations
About the editors
Hongbo Deng is Senior Staff Engineer and Director in the Search and Recommendation Business Unit at Alibaba Group. Before that, he was a senior software engineer at Google, and a senior research scientist at Yahoo! Labs. His research interests include information retrieval, web search, data mining, recommendation system, natural language processing. He won the Best Paper Award in SIGKDD 2016, and the Vannevar Bush Best Paper Award in JCDL 2012. He is a senior member of ACM.
Bibliographic Information
Book Title: Query Understanding for Search Engines
Editors: Yi Chang, Hongbo Deng
Series Title: The Information Retrieval Series
DOI: https://doi.org/10.1007/978-3-030-58334-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-58333-0Published: 02 December 2020
Softcover ISBN: 978-3-030-58336-1Published: 03 December 2021
eBook ISBN: 978-3-030-58334-7Published: 01 December 2020
Series ISSN: 1871-7500
Series E-ISSN: 2730-6836
Edition Number: 1
Number of Pages: X, 224
Number of Illustrations: 16 b/w illustrations, 5 illustrations in colour
Topics: Information Storage and Retrieval, Information Systems Applications (incl. Internet)