Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
Extracting semantic relations from query logs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Coherent keyphrase extraction via web mining
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Automatic hypertext keyphrase detection
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Data Mining and Knowledge Discovery
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Existing keyword suggestion tools from various search engine companies could automatically suggest keywords related to the advertisers' products or services, counting in simple statistics of the keywords, such as search volume, cost per click (CPC), etc. However, the nature of the generalized Second Price Auction suggests that better understanding the competitors' keyword selection and bidding strategies better helps to win the auction, other than only relying on general search statistics. In this paper, we propose a novel keyword suggestion strategy, called Competitive Analysis, to explore the keyword based competition relationships among advertisers and eventually help advertisers to build campaigns with better performance. The experimental results demonstrate that the proposed Competitive Analysis can both help advertisers to promote their product selling and generate more revenue to the search engine companies.