An integrated method for hierarchy construction of domain-specific terms

Understanding text requires not only the extraction of individual concepts, but the identification of semantic relationships among concepts as well. Lexical resources have been applied to analyzing text in a wide range of applications. However, manual compilation of lexical resources is difficult to keep up with the rapid increase of the volume and diversity of user-generated content on the web. Automatic concept hierarchy construction has been considered as one solution to the above problem. Despite extensive effort on automatic construction of concept hierarchies, few studies have focused on the concepts of specific domains. In this study, we propose a comprehensive framework for building a domain-specific concept hierarchy. By synthesizing different types of measurements of relatedness among concepts, we propose an integrated method for building a multi-branch hierarchy of product features from online consumer reviews. The experiment results show that the proposed algorithm successfully reconstructs almost an entire hierarchy except for missing a few concepts and links. Starting from scratch, the algorithm reconstructed about 60% of the manually constructed hierarchy. The proposed method can be used to improve search results by better understanding user queries, and to facilitate personalized recommendations in e-commerce.