The Information Retrieval Series
cover

Query Understanding for Search Engines

Editors: Chang, Yi, Deng, Hongbo (Eds.)

  • 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
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Buy this book

eBook 96,29 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: January 14, 2021
  • ISBN 978-3-030-58334-7
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 124,79 €
price for Spain (gross)
About this book

This book presents a systematic study of practices and theories for query understanding of search engines. These studies can be categorized into three major classes. The first class is to figure out what the searcher wants by extracting semantic meaning from the searcher’s keywords, such as query classification, query tagging, and query intent understanding. The second class is to analyze search queries and then translate them into an enhanced query that can produce better search results, such as query spelling correction or query rewriting. The third class is to assist users in refining or suggesting queries in order to reduce users’ search effort and satisfy their information needs, such as query auto-completion and query suggestion.
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.

About the authors

Yi Chang is the Dean of the School of Artificial Intelligence, Jilin University, China. Prior to this, he was Technical Vice President at Huawei Research America, and Research Director at Yahoo Research. His research interests include information retrieval, data mining, machine learning, natural language processing, and artificial intelligence. He has published more than 100 papers on premium conferences or journals, and was elected as an ACM Distinguished Scientist in 2018 for his contributions to intelligent algorithms for search engines.
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.

Buy this book

eBook 96,29 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: January 14, 2021
  • ISBN 978-3-030-58334-7
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 124,79 €
price for Spain (gross)
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Bibliographic Information

Bibliographic Information
Book Title
Query Understanding for Search Engines
Editors
  • Yi Chang
  • Hongbo Deng
Series Title
The Information Retrieval Series
Series Volume
46
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-58334-7
DOI
10.1007/978-3-030-58334-7
Hardcover ISBN
978-3-030-58333-0
Series ISSN
1871-7500
Edition Number
1
Number of Pages
X, 228
Number of Illustrations
10 b/w illustrations, 10 illustrations in colour
Topics