Competitive analysis from click-through log

ABSTRACT

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.

REFERENCES

• 1: V. Krishna. Auction Theory. Academic Press, 2002.
• 2: J. Norris. Markov Chains. Cambridge University Press, 1998.
• 3: Ricardo Baeza-Yates , Alessandro Tiberi, Extracting semantic relations from query logs, Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, August 12-15, 2007, San Jose, California, USA [doi>10.1145/1281192.1281204]
• 4: S. C. Deerwester, S. T. Dumais, T. K. Landauer, G. W. Furnas, and R. A. Harshman. Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6):391--407, 1990.
• 5: Mandar Mitra , Amit Singhal , Chris Buckley, Improving automatic query expansion, Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, p.206-214, August 24-28, 1998, Melbourne, Australia [doi>10.1145/290941.290995]
• 6: Turney, P.D., Coherent Keyphrase extraction via web mining. In Proc. of the 16th International Joint Conference on Artificial Intelligence (IJCAI-03), 2003.
• 7: Kelleher, D. and Luz, S., Automatic hypertext keyphrase detection. In Proc. of the 18th International Joint Conference on Artificial Intelligence (IJCAI-05), 2005.
• 8: Wen-tau Yih , Joshua Goodman , Vitor R. Carvalho, Finding advertising keywords on web pages, Proceedings of the 15th international conference on World Wide Web, May 23-26, 2006, Edinburgh, Scotland [doi>10.1145/1135777.1135813]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.5 On-line Information Services

Additional Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.4 Applications

General Terms:
Algorithms, Design, Experimentation, Performance

Keywords:
competitive analysis, keyword advertising, keyword suggestion