The DOI matches its Crossref record.
Corpus-based stemming using cooccurrence of word variants
Open accessAbstract
Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots. It is one of the simplest applications of natural-language processing to IR and is one of the most effective in terms of user acceptance and consistency, though small retrieval improvements. Current stemming techniques do not, however, reflect the language use in specific corpora, and this can lead to occasional serious retrieval failures. We propose a technique for using corpus-based word variant cooccurrence statistics to modify or create a stemmer. The experimental results generated using English newspaper and legal text and Spanish text demonstrate the viability of this technique and its advantages relative to conventional approaches that only employ morphological rules.
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Cited by
Discourse Segmentation of Multi-Party Conversation
Galley, M., McKeown, K., Fosler-Lussier, E., & Jing, H. (2003) · Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - ACL '03 · doi:10.3115/1075096.1075167 · Cited by 351
Resolving ambiguity for cross-language retrieval
Ballesteros, L., & Croft, W. B. (1998) · Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/290941.290958 · Cited by 309
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Metadata
- Authors
- Xu, J., & Croft, W. B.
- Venue
- ACM Transactions on Information Systems
- Published
- 1998-01
- Volume
- 16
- Issue
- 1
- Pages
- 61-81
- ISSN
- 1046-8188 (ISSN-L)
- 1558-2868
- OpenAlex
- W2008495066
- Cited by
- 305
- References
- 0
- FWCI
- 7.44
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.