Semantic classification of posts in social networks by means of concept hierarchies
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
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A general automatic domain concept hierarchy construction procedure is presented in this paper. This is a domain independent construct a domain concept hierarchy from a domain corpus . The construction procedure mainly includes domain terminology extraction, word sense disambiguation, similarity computation, hierarchy construction and subsumption relation detection. All extracted candidate terms are ranked first, then one can select the top terms as domain terminologies. Frequency ratio and entropy of a word are considered to rank candidate terms. Relations between terms are taken into account for words in WordNet, while distributional similarity is used to compute similarity between words outside WordNet. Experiments on two domain corpus show that the proposed procedure is feasible and can get reasonable concept hierarchy.