A scoring algorithm based on retrieval term expansion

Jiayu Yang; Songming Zou; Runze Ye

doi:10.1117/12.2641008

13 October 2022 A scoring algorithm based on retrieval term expansion

Jiayu Yang, Songming Zou, Runze Ye

Proceedings Volume 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022); 122870H (2022) https://doi.org/10.1117/12.2641008
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 2022, Wuhan, China

Abstract

Information retrieval is the foundation of content-driven applications, and the quality of the search results directly affects whether users can quickly obtain the required information. At present, vertical search engines for specific fields meet the needs of users to obtain specific information to some extents, but full-text search engines based on text matching cannot search from the perspective of semantics, so that search results strongly dependent on the selection of search terms. Aiming at the above problems, a scoring and sorting algorithm based on search term expansion is proposed. This method combines the research contents of search term expansion based on relational ontology and semantic similarity calculation based on word vector, discusses the search strategy for learning data library, and proposes a reasonable expansion method for search terms in vertical search engines. The Dscore ranking algorithm of search results proposes a new optimization strategy for the ranking algorithm of search results, realizing a search engine more suitable for library applications.

Citation Download Citation

Jiayu Yang, Songming Zou, and Runze Ye "A scoring algorithm based on retrieval term expansion", Proc. SPIE 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 122870H (13 October 2022); https://doi.org/10.1117/12.2641008

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