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Record Nr. |
UNISA996465457003316 |
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Titolo |
Query understanding for search engines / / editors, Yi Chang and Hongbo Deng |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2020] |
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©2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (X, 224 p. 21 illus., 5 illus. in color.) |
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Collana |
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The Information Retrieval Series, , 1871-7500 ; ; 46 |
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Disciplina |
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Soggetti |
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Information retrieval |
Information Systems Applications (incl. Internet) |
Information organization |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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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Sommario/riassunto |
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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, |
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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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