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.
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)
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)
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. Bergmann, and A. Stahl. Advances in Case-Based Reasoning, Proceedings of the 4th European Workshop on Case-Based Reasoning, EWCBRY98, Dublin, Ireland, page 25--36. Berlin, Springer-Verlag, (1998)
D. Bollegala, Y. Matsuo, and M. Ishizuka. WWW '07: Proceedings of the 16th international conference on World Wide Web, page 757--766. New York, NY, USA, ACM, (2007)
C. Cattuto, D. Benz, A. Hotho, and G. Stumme. The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008, volume 5318 of LNAI, page 615--631. Heidelberg, Springer, (2008)
C. Cattuto, D. Benz, A. Hotho, and G. Stumme. Proceedings of the 3rd Workshop on Ontology Learning and Population (OLP3), page 39--43. Patras, Greece, (July 2008)
C. Cattuto, D. Benz, A. Hotho, and G. Stumme. Proc. Intl. Semantic Web Conference, volume 5318 of LNAI, page 615--631. Berlin/Heidelberg, Springer, (2008)
A. Correya, R. Hennequin, and M. Arcos. (2018)cite arxiv:1808.10351Comment: Music Information Retrieval, Cover Song Identification, Million Song Dataset, Natural Language Processing.