Abductive Reasoning for Keyword Recovering in Semantic-Based Keyword Extraction

Abstract

This paper proposes semantic based keyphrase recovery for domain-independent keyphrase extraction. In this method, we add a keyphrase recovery function as a post- process of the conventional keyphrase extractors in order to reconsider the failed keyphrases by semantic matching based on sentence meaning. We also add the Domain Identification Function to determine the related domain of the keyphrases by using keyphrases extracted from the conventional systems in order to make the system as domain-independent. The semantic matching is performed to compare the similar meanings between ones of failed keyphrases and ones in the knowledge base. Therefore, the failed keyphrases that are matched by semantic matching are recused as keyphrases. The experiments with the summary sentences in 60 articles of IEICE Transactions on Information and Systems and glossaries from four resources are performed in initializing Domain Knowledge Base. Other summary sentences in 100 articles of IEICE Transactions on Information and Systems and in 15 chapters in a Computer Information System textbook are experimented in recovering the failed keyphrases. The results reveal that the proposed method increases the average performance of conventional EXTRACTOR and KEA approximately by 33.16 and 41.30% of precision, and 36.10 and 39.17% of recall, respectively.