Clustering abstracts instead of full texts
- Authors
- Makagonov, Pavel; Alexandrov, Mikhail; Gelbukh, Alexander
- Issue Date
- 2004
- Publisher
- SPRINGER-VERLAG BERLIN
- Citation
- TEXT, SPEECH AND DIALOGUE, PROCEEDINGS, v.3206, pp 129 - 135
- Pages
- 7
- Journal Title
- TEXT, SPEECH AND DIALOGUE, PROCEEDINGS
- Volume
- 3206
- Start Page
- 129
- End Page
- 135
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/65593
- DOI
- 10.1007/978-3-540-30120-2_17
- ISSN
- 0302-9743
1611-3349
- Abstract
- Accessibility of digital libraries and other web-based repositories has caused the illusion of accessibility of the full texts of scientific papers. However, in the majority of cases such an access (at least free access) is limited only to abstracts having no more then 50-100 words. Traditional keyword-based approach for clustering this type of documents gives unstable and imprecise results. We show that they can be easy improved with more adequate keyword selection and document similarity evaluation. We suggest simple procedures for this. We evaluate our approach on the data from two international conferences. One of our conclusions is the suggestion for the digital libraries and other repositories to provide document images of full texts of the papers along with their abstracts for open access via Internet.
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Collections - College of Engineering > School of Chemical Engineering and Material Science > 1. Journal Articles
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