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Competitor mining with the web
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DOI：10.1109/TKDE.2008.98.png)
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Abstract
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This paper is concerned with the problem of mining competitors from the Web automatically. Nowadays, the fierce competition in the market necessitates every company to know not only which companies are its primary competitors but also in which domains 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 domains, 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 domains in which the given entity and its competitors play against each other, and 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. A total of 728 competitors and 3,640 competitive domains with 6,381 competitive evidences are discovered with the prototype. The experimental results show that the proposed algorithm is highly effective.
Keywords:
information search and retrieval
content analysis and indexing
performance evaluation
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