Query log data for ad targeting
A WWW2006 paper out of Microsoft Research, "Finding Advertising Keywords on Web Pages" (PDF), claims that query log data is particularly useful for ad targeting.
Specifically, the researchers extracted from MSN query logs the keywords some people used to find a given page. They tested using that as one of many features for ad targeting. In their results, it was one of the most effective features.
Very interesting. It has always been harder to target ads to content than to search results because intent is much less clear.
By using the query log data in this way, the researchers were effectively using the intent of the searchers that arrived at the page as a proxy for the intent of everyone who arrived at the page.
Query log data for ad targeting
A WWW2006 paper out of Microsoft Research, "Finding Advertising Keywords on Web Pages" (PDF), claims that query log data is particularly useful for ad targeting.
Specifically, the researchers extracted from MSN query logs the keywords some people used to find a given page. They tested using that as one of many features for ad targeting. In their results, it was one of the most effective features.
Very interesting. It has always been harder to target ads to content than to search results because intent is much less clear.
By using the query log data in this way, the researchers were effectively using the intent of the searchers that arrived at the page as a proxy for the intent of everyone who arrived at the page.
With this Web page, we are opening some aspects of hakia R&D to the view of our users. We undertook highly specific research tasks solely dedicated to the advancement of the core-competency in Web search. The main challenge is to make science work in a co
D. Benz, B. Krause, G. Kumar, A. Hotho, and G. Stumme. Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009), Bled, Slovenia, (September 2009)
R. Baeza-Yates, and A. Tiberi. KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, page 76--85. New York, NY, USA, ACM, (2007)description = Extracting semantic relations from query logs,
location = San Jose, California, USA,
isbn = 978-1-59593-609-7,
doi = http://doi.acm.org/10.1145/1281192.1281204.
R. Baeza-Yates, and A. Tiberi. KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, page 76--85. New York, NY, USA, ACM, (2007)
Q. Zhao, S. Hoi, T. Liu, S. Bhowmick, M. Lyu, and W. Ma. WWW '06: Proceedings of the 15th international conference on World Wide Web, page 543--552. New York, NY, USA, ACM Press, (2006)
R. Baeza-Yates, and A. Tiberi. KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, page 76--85. New York, NY, USA, ACM, (2007)description = Extracting semantic relations from query logs,
location = San Jose, California, USA,
isbn = 978-1-59593-609-7,
doi = http://doi.acm.org/10.1145/1281192.1281204.
Q. Zhou, C. Wang, M. Xiong, H. Wang, and Y. Yu. Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC/ASWC2007), Busan, South Korea, volume 4825 of LNCS, page 687--700. Berlin, Heidelberg, Springer Verlag, (November 2007)