Zobrazeno 1 - 10
of 5 910
pro vyhledávání: '"DOCUMENT RETRIEVAL"'
Publikováno v:
Journal of Information Science Theory and Practice, Vol 12, Iss 3 (2024)
The information retrieval (IR) process often encounters a challenge known as query-document vocabulary mismatch, where user queries do not align with document content, impacting search effectiveness. Automatic query expansion (AQE) techniques aim to
Externí odkaz:
https://doaj.org/article/3dd35ba4dbd847478177b4fa4d0d847c
Publikováno v:
IEEE Access, Vol 11, Pp 27942-27954 (2023)
Previous scientific literature retrieval methods, which are based on mathematical expression, ignore the literature attributes and the association between the literature, and the retrieval accuracy was affected. In this study, literature retrieval mo
Externí odkaz:
https://doaj.org/article/fdcc39a5d4644d1b84f8936195566b3b
Autor:
Harun Bolat, Baha Şen
Publikováno v:
Applied Sciences, Vol 14, Iss 6, p 2613 (2024)
In this paper, we describe our biomedical document retrieval system and answers extraction module, which is part of the biomedical question answering system. Approximately 26.5 million PubMed articles are indexed as a corpus with the Apache Lucene te
Externí odkaz:
https://doaj.org/article/c299ee39aef445e8ad8cfd00cb7fff49
Akademický článek
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Akademický článek
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Publikováno v:
Applied Sciences, Vol 13, Iss 24, p 13075 (2023)
The lack of quality in scientific documents affects how documents can be retrieved depending on a user query. Existing search tools for scientific documentation usually retrieve a vast number of documents, of which only a small fraction proves releva
Externí odkaz:
https://doaj.org/article/36fc402872f94a93b2ffa414ff05685a
Publikováno v:
Applied Sciences, Vol 13, Iss 24, p 13177 (2023)
Open-domain question answering requires the task of retrieving documents with high relevance to the query from a large-scale corpus. Deep learning-based dense retrieval methods have become the primary approach for finding related documents. Although
Externí odkaz:
https://doaj.org/article/427506565f4b4d24b2d836a715a5c408
Autor:
Ziyang Feng, Xuedong Tian
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11207 (2023)
Achieving scientific document retrieval by considering the wealth of mathematical expressions and the semantic text they contain has become an inescapable trend. Current scientific document matching models focus solely on the textual features of expr
Externí odkaz:
https://doaj.org/article/1b4b08ef8488419b9bb051fd695639df
Publikováno v:
Mathematical Biosciences and Engineering, Vol 19, Iss 5, Pp 4976-4990 (2022)
In a retrieval system for mathematical documents based on mathematical expressions, the input and matching of mathematical expressions are key steps that affect the system's usability, accessibility and efficiency because of their special attributes.
Externí odkaz:
https://doaj.org/article/2b0e97caf584453c8f80f157d681ad53
Publikováno v:
Mathematical Biosciences and Engineering, Vol 19, Iss 4, Pp 3748-3766 (2022)
Scientific documents contain a large number of mathematical expressions and texts containing mathematical semantics. Simply using mathematical expressions or text to retrieve scientific documents can hardly meet retrieval needs. The real difficulty i
Externí odkaz:
https://doaj.org/article/efab8e67da8e4869b08686a4774935f5