Estimating Point-of-View-based Similarity Using POV Reinforcement and Similarity Propagation
Kenji Nagamatsu, Hidehiko Tanaka · Institutional Repositories DataBase (IRDB) · 1996
This paper . proposes a similarity measure which takes account of pointof-views (abbreviated to POV, hereafter) in the calculation of similarity values. So far many researches on similarity measures have been performed but none takes account of POVs. The similarity measure proposed in this paper is based on co-occurrence probabilities of words and this makes it possible to obtain preferable precision even if POVs are not given. This method consists of two parts of processes, POV reinforcement and similarity propagation. First, the POV reinforcement process, which affects the similarity between words, modifies the weights of links according to the relatedness between the link and the POV word. Second, the similarity propagation process propagates the weights of links and defines a similarity value for word pairs which do not actually cooccur in the corpus. Using those two processes this method becomes capable both to take POVs into consideration and to cope with the sparseness of corpora to some degree. This paper, however, focuses on the POV reinforcement and evaluates the effectiveness of the method..