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.

作为一个新兴平台，在线问答（Q＆A）社区正在成为有价值的语料库来源，可以反映专家消费者对可比实体的看法。在这项研究中，提出了一种从在线问答内容中识别可比实体的新方法，可以有效地从在线问答社区中提取可比实体。在ICQA中，首先利用基于模式的方法和基于监督学习的方法的优势来提取候选实体。然后，通过考虑问答内容中的信誉差异和实体相关性来构建实体比较网络，以分析实体之间的竞争力并相应地从候选实体中提取可比较的实体。因此，在相同的方法框架内，对于经理或消费者指定的给定实体，可以同时确定可比较的实体及其竞争力等级。以汽车行业为实验背景，通过有关可比实体识别和可比实体排名的综合实验证明了ICQA的有效性。实验结果表明，与最先进的方法相比，ICQA可以识别出更准确，更广泛的可比实体，找到其他方法所忽略的新颖实体，并提供更可靠的可比实体等级特征，被认为可用于经理和消费者都可以根据在线问答内容做出合理的决定。以汽车行业为实验背景，通过有关可比实体识别和可比实体排名的综合实验证明了ICQA的有效性。实验结果表明，与最先进的方法相比，ICQA可以识别出更准确，更广泛的可比实体，找到其他方法所忽略的新颖实体，并提供更可靠的可比实体等级特征，被认为可用于经理和消费者都可以根据在线问答内容做出合理的决定。以汽车行业为实验背景，通过有关可比实体识别和可比实体排名的综合实验证明了ICQA的有效性。实验结果表明，与最先进的方法相比，ICQA可以识别出更准确，更广泛的可比实体，找到其他方法所忽略的新颖实体，并提供更可靠的可比实体等级特征，被认为可用于经理和消费者都可以根据在线问答内容做出合理的决定。