MeSH-Based Semantic Indexing Approach to Enhance Biomedical Information Retrieval

被引:8
|
作者
Kammoun, Hager [1 ]
Gabsi, Imen [2 ]
Amous, Ikram [3 ]
机构
[1] Sfax Univ, MIRACL FS, Rd Sokra Km 3, Sfax 3018, Tunisia
[2] Sfax Univ, MIRACL FSEG, Rd Aeroport Km 4, Sfax, Tunisia
[3] Sfax Univ, MIRACL ENETCOM, Rd Tunis Km 10, Sfax 3018, Tunisia
来源
COMPUTER JOURNAL | 2022年 / 65卷 / 03期
关键词
semantic indexing; word sense disambiguation; semantic similarity measure; representation enrichment strategy; information retrieval; WORD SENSE DISAMBIGUATION; SIMILARITY; RELATEDNESS; MODEL;
D O I
10.1093/comjnl/bxaa073
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Owing to the tremendous size of electronic biomedical documents, users encounter difficulties in seeking useful biomedical information. An efficient and smart access to the relevant biomedical information has become a fundamental need. In this research paper, we set forward a novel biomedical MeSH-based semantic indexing approach to enhance biomedical information retrieval. The proposed semantic indexing approach attempts to strengthen the content representation of both documents and queries by incorporating unambiguous MeSH concepts as well as the adequate senses of ambiguous MeSH concepts. For this purpose, our proposed approach relies on a disambiguation method to identify the adequate senses of ambiguous MeSH concepts and introduces four representation enrichment strategies so as to identify the best appropriate representatives of the adequate sense in the textual entities representation. To prove its effectiveness, the proposed semantic indexing approach was evaluated by intensive experiments. These experiments were carried out on OHSUMED test collection. The results reveal that our proposal outperforms the state-of-the-art approaches and allow us to highlight the most effective strategy.
引用
收藏
页码:516 / 536
页数:21
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