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- W2149441129 abstract "Inner structures of Chinese lexical concepts have embedded some useful semantic relations. In this paper, we proposed a new statistical approach to mine lexical hyponymy relations from large-scale concept set, instead of analyzing inner structures. Firstly we designed common suffix tree to cluster the lexical concept set. Class concepts are then extracted by statistic-base rules we investigated in concept set. Finally, we export hyponymy relations from the common suffix tree. Experimental result showed us that this approach achieved a precision of 95.833% and a recall of 67.241% when the concept size achieved 800,000." @default.
- W2149441129 created "2016-06-24" @default.
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- W2149441129 date "2008-07-01" @default.
- W2149441129 modified "2023-10-14" @default.
- W2149441129 title "Mining lexical hyponymy relations from large-scale concept set" @default.
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- W2149441129 doi "https://doi.org/10.1109/icmlc.2008.4620418" @default.
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