Abstract
We have developed a summarization method that creates a summary suitable for the process of sifting information retrieval results. Conventional methods extract important sentences to produce summaries that tend to be long and complex. We have developed the phrase-representation summarization method that constructs short phrases to reduce the burden of reading such long sentences. Each phrase is constructed by (1) dependency analysis to extract the relations between words, (2) selection of the core relation from dependency relations, (3) adding relations necessary for the unity of the phrase's meaning, and (4) generation of the surface phrase from the constructed graph. To evaluate the effectiveness of this method, we have developed an improved task-based evaluation method of summarization, the accuracy of which is increased by specifying the details of the task including background stories, and by assigning ten subjects per summary sample. The method also serves precision/recall pairs for a variety of situations by introducing multiple levels of relevance assessment. The method is applied to prove that phrase-represented summary is most effective to select relevant documents from information retrieval results. Theresult comes from the fact that the constructed phrases are rather short but cover more important keywords.
