Issue No. 10 - October (2008 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2008.98
Shenghua Bao , Shanghai Jiao Tong University, Shanghai
Rui Li , Shanghai Jiao Tong University, Shanghai
Yong Yu , Shanghai Jiao Tong University, Shanghai
Yunbo Cao , Microsoft Research Asia, Beijing
This paper is concerned with the problem of mining competitors from the web automatically. Nowadays the fierce competition in the market necessitates every company not only to know which companies are its primary competitors, but also in which fields the company's rivals compete with itself and what its competitors' strength is in a specific competitive domain. The task of competitor mining that we address in the paper includes mining all the information such as competitors, competing fields and competitors' strength. A novel algorithm called CoMiner is proposed, which tries to conduct a web-scale mining in a domain-independent manner. The CoMiner algorithm consists of three parts: 1) given an input entity, extracting a set of comparative candidates and then ranking them according to comparability; 2) extracting the fields in which the given entity and its competitors play against each other; 3) identifying and summarizing the competitive evidence that details the competitors' strength. As for evaluation, a prototype system implementing the CoMiner algorithm is presented. An evaluation data set consisting of 70 entities is constructed. 728 competitors and 3,640 competitive fields with 6,381 competitive evidences are discovered with the prototype. The experimental results show that the proposed algorithm is highly effective.
Content Analysis and Indexing, Information Search and Retrieval, Performance evaluation
Y. Yu, S. Bao, R. Li and Y. Cao, "Competitor Mining with the Web," in IEEE Transactions on Knowledge & Data Engineering, vol. 20, no. , pp. 1297-1310, 2008.