The Open Automation and Control Systems Journal

2014, 6 : 473-479
Published online 2014 December 31. DOI: 10.2174/1874444301406010473
Publisher ID: TOAUTOCJ-6-473

MeSH-based Biomedical Information Semantic Retrieval Model

Qichen Han , Dongmei Li , Jiaxing Tan , Xuan Wang , Bo Fang and Xuan Tian
e School of Information Science and Technology, Beijing Forestry University, Beijing, China, 100083.

ABSTRACT

The subject headings is an approach that improves information search accuracy and comprehensiveness to approach multi-language search and intellectualized concept retrieval. Using this method in network information retrieval tool will improve the efficiency of information retrieval. This paper proposes an idea of calculating the similarity based on the relationship among the words in the subject headings. Utilizing query extension, we create a MeSH (Medical Subject Headings)-based Biomedical Information Semantic Retrieval Model (MBISRM). Finally, we compare the results from MBISRM and Baidu in two category realms. The search results from MBISRM are preferable to that of Baidu overall. This paper offers a new stream of thought on applying subject headings in network information system.

Keywords:

MeSH, Semantic Retrieval, Similarity Computation, Query Extension, Standardization, Weighted Sort.