Identifying comparable entities from online question-answering contents

•A method ICQA is proposed for comparable entity identification from Q&A contents.•ICQA identifies comparable entities in comparative and non-comparative sentences.•The performance of ICQA is validated with real-world Q&A contents. As an emerging platform, online question-answering (Q&A) communities are becoming valuable corpus sources that reflect the opinions of expert consumers on comparable entities. In this study, a novel method-Identifying Comparable entities from online Question-Answering contents (ICQA)-is proposed to effectively extract comparable entities from online Q&A communities. In ICQA, candidate entities are firstly extracted by utilizing the advantages of pattern-based methods and supervised learning-based methods. An entity comparison network is then built by considering the credibility difference and entity relatedness in Q&A contents to analyze competitiveness between entities and extract comparable entities from candidate entities accordingly. Thus, within the same method framework, comparable entities and their competitiveness ranks can be simultaneously identified for a given entity specified by managers or consumers. By taking the automotive industry as the experimental background, the effectiveness of ICQA is demonstrated with comprehensive experiments regarding comparable entity identification and comparable entity ranking. Experimental results demonstrate that compared with state-of-the-art methods, ICQA can identify more accurate and broader comparable entities, find novel entities ignored by other methods, and provide a more solid comparable entity rank-features that are deemed desirable and applicable for both managers and consumers in making rational decisions based on online Q&A contents.