|This article's factual accuracy may be compromised due to out-of-date information. (February 2013)|
Personalized search refers to search experiences that are tailored specifically to an individual's interests by incorporating information about the individual beyond specific query provided. Pitkow et al. describe two general approaches to personalizing search results, one involving modifying the user’s query and the other re-ranking search results.
While many search engines take advantage of information about people in general, or about specific groups of people, personalized search depends on a user profile that is unique to the individual. Research systems that personalize search results model their users in different ways. Some rely on users explicitly specifying their interests or on demographic/cognitive characteristics. But user supplied information can be hard to collect and keep up to date. Others have built implicit user models based on content the user has read or their history of interaction with Web pages.
There are several publicly available systems for personalizing Web search results (e.g., Google Personalized Search and Bing's search result personalization). However, the technical details and evaluations of these commercial systems are proprietary.
Several concerns have been brought up regarding personalized search. It decreases the likelihood of finding new information by biasing search results towards what the user has already found. It introduces potential privacy problems in which a user may not be aware that their search results are personalized for them, and wonder why the things that they are interested in have become so relevant. The feature also has profound effects on the search engine optimization industry, due to the fact that search results will no longer be ranked the same way for every user.
- Pitokow, James; Hinrich Schütze, Todd Cass, Rob Cooley, Don Turnbull, Andy Edmonds, Eytan Adar, Thomas Breuel (2002). "Personalized search". Communications of the ACM (CACM) 45 (9): 50–55.
- Ma, Z.; Pant, G., and Sheng, O. (2007). "Interest-based personalized search.". ACM TOIS 25 (5).
- Frias-Martinez, E.; Chen, S.Y., and Liu, X. (2007). "Automatic cognitive style identification of digital library users for personalization.". JASIST 58 (2): 237–251.
- Chirita, P.; Firan, C., and Nejdl, W. (2006). "Summarizing local context to personalize global Web search". SIGIR: 287–296.
- Dou, Z.; Song, R., and Wen, J.R. (2007). "A large-scale evaluation and analysis of personalized search strategies". WWW: 581–590.
- Shen, X.; Tan, B. and Zhai, C.X. (2005). "Implicit user modeling for personalized search". CIKM: 824–831.
- Sugiyama, K.; Hatano, K., and Yoshikawa, M. (2004). "Adaptive web search based on user profile constructed without any effort from the user". WWW: 675–684.
- Teevan, J.; Dumais, S.T., and Horvitz, E. (2005). "Personalizing search via automated analysis of interests and activities". SIGIR: 415–422.
- Crook, Aidan, and Sanaz Ahari. "Making search yours". Bing. Retrieved 14 March 2011.
- "Google Personalized Results Could Be Bad for Search". Network World. Retrieved July 12, 2010.
- "Search Engines and Customized Results Based on Your Internet History". SEO Optimizers. Retrieved 27 February 2013.