Journal article
Vocabulary mining for information retrieval: rough sets and fuzzy sets
Information processing & management, Vol.37(1), pp.15-38
2001
DOI: 10.1016/S0306-4573(00)00014-5
Abstract
Vocabulary mining in information retrieval refers to the utilization of the domain vocabulary towards improving the user’s query. Most often queries posed to information retrieval systems are not optimal for retrieval purposes. Vocabulary mining allows one to generalize, specialize or perform other kinds of vocabulary-based transformations on the query in order to improve retrieval performance. This paper investigates a new framework for vocabulary mining that derives from the combination of rough sets and fuzzy sets. The framework allows one to use rough set-based approximations even when the documents and queries are described using weighted, i.e., fuzzy representations. The paper also explores the application of generalized rough sets and the variable precision models. The problem of coordination between multiple vocabulary views is also examined. Finally, a preliminary analysis of issues that arise when applying the proposed vocabulary mining framework to the Unified Medical Language System (a state-of-the-art vocabulary system) is presented. The proposed framework supports the systematic study and application of different vocabulary views in information retrieval.
Details
- Title: Subtitle
- Vocabulary mining for information retrieval: rough sets and fuzzy sets
- Creators
- Padmini Srinivasan - School of Library and Information Science, The University of Iowa, Iowa City, IO 52242, USAMiguel E Ruiz - School of Library and Information Science, The University of Iowa, Iowa City, IO 52242, USADonald H Kraft - Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803-4020, USAJianhua Chen - Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803-4020, USA
- Resource Type
- Journal article
- Publication Details
- Information processing & management, Vol.37(1), pp.15-38
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/S0306-4573(00)00014-5
- ISSN
- 0306-4573
- eISSN
- 1873-5371
- Language
- English
- Date published
- 2001
- Academic Unit
- Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984003013302771
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