TY - GEN
T1 - A fuzzy-rough set based semantic similarity measure between cross-lingual documents
AU - Huang, Hsun Hui
AU - Yang, Horng Chang
AU - Kuo, Yau Hwang
PY - 2008
Y1 - 2008
N2 - As cross-lingual information retrieval attracts increasing attention, tools that measure cross-lingual document similarity become desirable. Since the way that people convey thoughts at the abstract concept level makes little, if any, difference in the languages they use, it is possible to measure semantic similarity between different lingual documents based on the concepts conveyed by the documents. In this paper, a novel fuzzy rough set based method for measurement of semantic similarity between cross lingual (Chinese and English) documents is proposed. Aided by a bilingual dictionary and Wordnet, translation is processed like word sense disambiguation and all the distilled senses are used to construct a fuzzy approximation space using a fuzzy partition algorithm. In the fuzzy approximation space documents are approximated by their fuzzy upper and lower approximations and the similarity measure is defined accordingly. The upper and lower approximations correspond to the slack and tight extent of the concepts in their associated document. This method makes possible to distinguish among the documents whose original texts seem not similar but conveyed concepts are similar.
AB - As cross-lingual information retrieval attracts increasing attention, tools that measure cross-lingual document similarity become desirable. Since the way that people convey thoughts at the abstract concept level makes little, if any, difference in the languages they use, it is possible to measure semantic similarity between different lingual documents based on the concepts conveyed by the documents. In this paper, a novel fuzzy rough set based method for measurement of semantic similarity between cross lingual (Chinese and English) documents is proposed. Aided by a bilingual dictionary and Wordnet, translation is processed like word sense disambiguation and all the distilled senses are used to construct a fuzzy approximation space using a fuzzy partition algorithm. In the fuzzy approximation space documents are approximated by their fuzzy upper and lower approximations and the similarity measure is defined accordingly. The upper and lower approximations correspond to the slack and tight extent of the concepts in their associated document. This method makes possible to distinguish among the documents whose original texts seem not similar but conveyed concepts are similar.
UR - https://www.scopus.com/pages/publications/52449110754
UR - https://www.scopus.com/pages/publications/52449110754#tab=citedBy
U2 - 10.1109/ICICIC.2008.33
DO - 10.1109/ICICIC.2008.33
M3 - Conference contribution
AN - SCOPUS:52449110754
SN - 9780769531618
T3 - 3rd International Conference on Innovative Computing Information and Control, ICICIC'08
BT - 3rd International Conference on Innovative Computing Information and Control, ICICIC'08
T2 - 3rd International Conference on Innovative Computing Information and Control, ICICIC'08
Y2 - 18 June 2008 through 20 June 2008
ER -