1University of Chinese Academy of Sciences, Beijing 100049, China 2National Science Library, Chinese Academy of Sciences, Beijing 100190, China 3National Library of China, Beijing 100081, China
[Objective] This paper uses Distributional Semantics to build high quality lexical chains. [Methods] First, we built an algorithm using WordNet Thesaurus to compute the semantic relations among language units of the texts. Second, we adopted the Distributional Memory Model to compute their latent semantic relations. Finally, we combined these relations to build the lexical chains, which were examined with papers from medical science. [Results] The proposed algorithm was better than the non-greedy methods to describe the papers’ topics. [Limitations] The efficiency of the algorithm needs to be improved. It should also be examined with papers from other fields. [Conclusions] The proposed model can detect the latent semantic relation, and then improve the quality of lexical chains building with phrases.
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