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[ subject:"Search engines." ]
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Query understanding for search engines
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Chang, Yi.
Query understanding for search engines
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Query understanding for search enginesedited by Yi Chang, Hongbo Deng.
其他作者:
Chang, Yi.
出版者:
Cham :Springer International Publishing :2020.
面頁冊數:
x, 224 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Search engines.
電子資源:
https://doi.org/10.1007/978-3-030-58334-7
ISBN:
9783030583347$q(electronic bk.)
Query understanding for search engines
Query understanding for search engines
[electronic resource] /edited by Yi Chang, Hongbo Deng. - Cham :Springer International Publishing :2020. - x, 224 p. :ill., digital ;24 cm. - The information retrieval series,v.461871-7500 ;. - Information retrieval series ;v.37..
1. An Introduction to Query Understanding -- 2. Query Classification -- 3. Query Segmentation and Tagging -- 4. Query Intent Understanding -- 5. Query Spelling Correction -- 6. Query Rewriting -- 7. Query Auto-Completion -- 8. Query Suggestion -- 9. Future Directions of Query Understanding.
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.
ISBN: 9783030583347$q(electronic bk.)
Standard No.: 10.1007/978-3-030-58334-7doiSubjects--Topical Terms:
250061
Search engines.
LC Class. No.: ZA4230 / .Q47 2020
Dewey Class. No.: 005.758
Query understanding for search engines
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1. An Introduction to Query Understanding -- 2. Query Classification -- 3. Query Segmentation and Tagging -- 4. Query Intent Understanding -- 5. Query Spelling Correction -- 6. Query Rewriting -- 7. Query Auto-Completion -- 8. Query Suggestion -- 9. Future Directions of Query Understanding.
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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.
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