Hong Cui
ABSTRACT
In this paper, we explore an approach to make better use of semi-structured documents in information retrieval in the domain of biology. Using machine learning techniques, we make those inherent structures explicit by XML markups. This marking up has great potentials in improving task performance in specimen identification and the usability of online flora and fauna.
- Flora of North America (http://hua.huh.harvard.edu/FNA/). {Accessed 11 February 2002}Google Scholar
- McCallum, A. K. Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering.http://www.cs.cmu.edu/~mccallum/bow 1996Google Scholar
- Burges, C.J.C A Tutorial on Support Vector Machines for pattern recognition. Knowledge Discovery and Data Mining, 2(2), 1998 Google ScholarDigital Library
- Joachims, T. Text categorization with Support Vector Machines: Learning with many relevant features. In European Conference on Machine Learning (ECML-98), 1998 Google ScholarDigital Library
- Soderland, Stephen. Learning Information Extraction Rules for Semi-structured and Free Text. Machine Learning, 44(1-3):233--272, 1999 Google ScholarDigital Library
Index Terms
- An approach to automatic classification of text for information retrieval
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