Term clustering using a corpus-based similarity measure

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2448, Issue , 2002, Pages 151-154

  Nenadić, Goran ^a   Spasić, Irena ^a   Ananiadou, Sophia ^a  

^a UNIVERSITY OF SALFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

MOLECULAR BIOLOGY;

BETWEEN CLUSTERS; CORPUS-BASED; LEXICAL SIMILARITY; NEAREST NEIGHBOUR; S-METHOD; SIMILARITY MATRIX; SIMILARITY MEASURE; TERM CLUSTERING;

CLUSTERING ALGORITHMS;

EID: 84942891998     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-46154-x_20     Document Type: Conference Paper

References (6)

1. Fasulo, D.: Analysis on Recent Work on Clustering Algorithms. Technical Report 01-03-02, University of Washington, Seattle (1999), p. 24.
2. Frantzi, K., Ananiadou, S., Mima, H.: Automatic Recognition of Multi-Word Terms. Int. J. on Digital Libraries 3/2 (2000), pp. 117–132.
3. Hearst, M.: Automatic Acquisition of Hyponyms From Large Text Corpora. Proc. of COLING 1992, Nantes, France (1992).
4. MEDLINE: National Library of Medicine. http://www.ncbi.nlm.nih.gov/PubMed/, (2002).
5. Mima, H., Ananiadou, S., Nenadić, G.: ATRACTWorkbench: An Automatic Term Recognition and Clustering of Terms. In: Matoušek, V. et al. (Eds.): Text, Speech and Dialogue – TSD 2001. LNAI 2166. Springer Verlag (2001), pp. 126–133.
6. Spasić, I., Nenadić, G., Manios, K., Ananiadou, S.: Supervised Learning of Term Similarities. Proc. of IDEAL 2002, Manchester, UK (2002).