Improving the performance of focused web crawlers
Data & Knowledge Engineering
Mining competitor relationships from online news: A network-based approach
Electronic Commerce Research and Applications
Efficient and domain-invariant competitor mining
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Social tie mining in company networks
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Mining competitive relationships by learning across heterogeneous networks
Proceedings of the 21st ACM international conference on Information and knowledge management
Learning to find comparable entities on the web
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Classifying Consumer Comparison Opinions to Uncover Product Strengths and Weaknesses
International Journal of Intelligent Information Technologies
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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 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.