{"title":"Applying domain knowledge and academic information to enhance unknown-item search in OPAC","authors":"Peerasak Intarapaiboon, Chainarong Kesamoon","doi":"10.22452/MJLIS.VOL24NO1.3","DOIUrl":null,"url":null,"abstract":"Many students usually use the unknown-item search strategies, including subject and keyword searches, to retrieve books or other materials provided in library catalogs. However, the success rates for unknown-item searching is relatively low compared with the known-item search strategies, i.e., title or author searches. In this paper, a framework for improving the unknown-item search is proposed. The main contributions of our framework concern both user's keywords and book indexing: (i) To enhance a user's keyword, the framework will select other relevant terms in a domain-related ontology; (ii) Topics expressed in course description are used as book indexing. A preliminary experiment shows that the proposed framework gives satisfactory results in terms of the numbers and the precision scores of retrieved books. Furthermore, the proposed interesting-score measure can facilitate to lift the precision levels.","PeriodicalId":45072,"journal":{"name":"Malaysian Journal of Library & Information Science","volume":" ","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Malaysian Journal of Library & Information Science","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.22452/MJLIS.VOL24NO1.3","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 3
Abstract
Many students usually use the unknown-item search strategies, including subject and keyword searches, to retrieve books or other materials provided in library catalogs. However, the success rates for unknown-item searching is relatively low compared with the known-item search strategies, i.e., title or author searches. In this paper, a framework for improving the unknown-item search is proposed. The main contributions of our framework concern both user's keywords and book indexing: (i) To enhance a user's keyword, the framework will select other relevant terms in a domain-related ontology; (ii) Topics expressed in course description are used as book indexing. A preliminary experiment shows that the proposed framework gives satisfactory results in terms of the numbers and the precision scores of retrieved books. Furthermore, the proposed interesting-score measure can facilitate to lift the precision levels.