Share, discover and discuss your life online
* Share content with friends, family and followers
* Discover new content, people and services around the web
* Discuss the content you share in real-time
Web search engines have changed our lives - enabling instant access to information about subjects that are both deeply important to us, as well as passing whims. The search engines that provide answers to our search queries also log those queries, in order to improve their algorithms. Academic research on search queries has shown that they can provide valuable information on diverse topics including word and phrase similarity, topical seasonality and may even have potential for sociology, as well as providing a barometer of the popularity of many subjects. At the same time, individuals are rightly concerned about what the consequences of accidental leaking or deliberate sharing of this information may mean for their privacy. In this talk I will cover the applications which have benefited from mining query logs, the risks that privacy can be breached by sharing query logs, and current algorithms for mining logs in a way to prevent privacy breaches.
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.
B. Krause, A. Hotho, and G. Stumme. Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008, 4956, page 101-113. Springer, (2008)
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. Jäschke, B. Krause, A. Hotho, and G. Stumme. Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008), AAAI Press, (2008)