Cross-domain ontology construction and alignment from online customer product reviews

Abstract

Online reviews often contain detailed sentiment towards different aspects of products and these opinions help consumers to be familiar with products. The introduction of domain ontology from online reviews may help consumers to obtain relevant information about products quickly. Nonetheless, they may compare products in multiple domains for purchase decisions. On this basis, the comparison of products in different domains induces that ontology alignment becomes a fundamental task to form a cross-domain ontology. However, due to large-scale text data and complex alignment mapping relations, many alignment algorithms are far from performing effectively. In this paper, a series of natural language processing approaches are applied to construct domain ontologies from online product reviews. Next, a new ontology alignment method is proposed to make purchase decisions regarding cross-domain product comparisons, in which a semantic-based algorithm and a structure-based algorithm are integrated to form a cross-domain ontology. Categories of experiments were conducted on reviews of smartphone and digital camera. Compared with benchmarked alignment tools, it shows that the proposed method yields to more accurate results. Finally, a case study with a customer friendly website is illustrated to present how the alignment of cross-domain ontology is able to help consumers on purchase decision support.