A retrieval method of similar question articles from web bulletin board

Abstract: This paper proposes a method for retrieving similar question articles from Web bulletin boards, which basically use the cosine similarity index derived from a user’s query sentence and article question sentences. Since these sentences are mostly short, it is difficult to distinguish whether article question sentences are similar to a user’s query sentence or not simply by applying the conventional cosine similarity index. In an attempt to overcome this problem, our method modifies the elements of the word vectors used in the cosine similarity index, which are derived from a sentence structure from the viewpoints of common words and non-common words between a user’s query sentence and article question sentences. Experimental results indicate that our proposed method is effective.