When you perform a search on one of the major search engines for a particular query, and when I perform the same search, chances are that we will see the same pages appearing on the search results pages. Then again, we may not. Chances are also good that in the future, the results that each of us sees will be different.
One of the areas that many in academia, and at commercial search engines are exploring is how to personalize web search.
We see that most visibly in the personalized search pages that the major search engines have released. They explain how to receive personalized searches on the following pages:
Google Help Center – Personalizing your search results
But, they don’t share too much about the personalization process itself on those pages. And, there’s some personalization of results happening when search results are returned regardless of whether or not a user of a search engine has signed to a personal search page.
I’ve listed many papers below that look at user behavior information and how it may be used to influence search results. I started with a small seed group of recent papers on personalization and mined their references for other papers that may help provide a bigger picture of the topic.
The papers go from an early discussion in 1998 on how PageRank can be personalized in “What can you do with a Web in your Pocket?” to collaborative filtering and user search histories and burstiness in search queries and the influence of geographic location to reranking search results based upon user profiles.
User queries are being studied, and an understanding of how different users can be from each other is the topic of at least one of these papers. Personalization based upon where we view search results, and upon how we view them, such as with mobile devices, is also being considered.
It’s pretty clear at this point that search engines see personalization as a means of providing a better experience for their users, and even as a key to providing more relevant results that meet individual users’ intentions when they search.
One of the measures that many site owners and consultants have used to see how visible a site is on the web is through ranking reports of placement for certain queries on the major search engines. That metric will become less and less useful, and that’s probably not a bad result.
A more meaningful measure is the number of visitors who arrive at a site, and interact with what they find there in a meaningful manner – whether it’s to buy something, or to find information, or to become a participant in some activity or become a member of a community.
There are a lot of different ways to personalize web searches, and many of the papers below provide insights into approaches that may lead to search engines that understand some of the differences between the different searchers that use their services. It’s not a complete list, and I’m sure that there are many more papers out on the web that should probably be included in a study on the growing personalization of search. But, I think that it’s a good introduction to the topic.
Papers
1998
What can you do with a Web in your Pocket? By Sergey Brin, Rajeev Motwani, Lawrence Page, Terry Winograd Data Engineering Bulletin, 21(2):37–47, 1998.
1999
Web Search Behavior of Internet Experts and Newbies By Christoph Hölscher & Gerhard Strube Proc. of WWW ’99, 1999.
2000
What Do Web Users Do? An Empirical Analysis of Web Use (pdf) By Andy Cockburn and Bruce McKenzie Int. J. Human-Computer Studies (2000)
SearchPad: Explicit Capture of Search Context to Support Web Search By Krishna Bharat Proceedings of WWW ‘00, 493-501.
Agglomerative clustering of a search engine query log (pdf) By Doug Beeferman and Adam Berger Proceedings of ACM SIGKDD international conference on Knowledge discovery and data mining, pages 407-416, 2000.
Real Life, Real Users, and Real Needs: A Study and Analysis of User Queries on the Web (pdf) By Major Bernard J. Jansen, Amanda Spink, and Tefko Saracevic Information Processing and Management, 36(2):207 { 227, 2000.
2001
Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments (pdf) By Alexandrin Popescul, Lyle H. Ungar, David M. Pennock, and Steve Lawrence Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI-2001), to appear, Morgan Kaufmann, San Francisco, 2001.
Capturing knowledge of user preferences: ontologies in recommender systems By Stuart E. Middleton, David C. De Roure, and Nigel R. Shadbolt Proceedings of the First International Conference on Knowledge Capture, K-CAP 2001
Improving the Effectiveness of Collaborative Filtering on Anonymous Web Usage Data (pdf) By Bamshad Mobasher, Honghua Dai, Tao Luo, and Miki Nakagawa Proceedings of Intelligent Techniques for Web Personalization ’01 (2001)
Web Site Personalizers for Mobile Devices (pdf) By Corin R. Anderson, Pedro Domingos, and Daniel S. Weld Proceedings of Intelligent Techniques for Web Personalization ’01 (2001)
Automated Query Generation For Embedded Information Retrieval (pdf) By Vladimir A. Kulyukin Proceedings of Intelligent Techniques for Web Personalization ’01 (2001)
2002
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization (pdf) By Bamshad Mobasher, Honghua Dai, Tao Luo, and Miki Nakagawa Data Mining and Knowledge Discovery, 6(1):61–82, 2002.
Personalized Search (pdf) By James Pitkow, Hinrich Schütze, Todd Cass, Rob Cooley, Don Turnbull, Andy Edmonds, Eytan Adar, and Thomas Breuel Communications of the ACM, 45(9):50–55, 2002.
Topic-Sensitive PageRank By Taher H. Haveliwala Proceedings of the Eleventh International World Wide Web Conference, 2002.
Persona: A Contextualized and Personalized Web Search (pdf) By Francisco Tanudjaja and Lik Mui Proceedings of the 35th Hawaii International Conference on System Sciences – 2002
2003
Coverage, Relevance, and Ranking: The Impact of Query Operators on Web Search Engine Results (pdf) By Caroline M. Eastman and Bernard J. Jansen TOIS, Vol. 21(4) (2003) 383–411
Finding Relevant Website Queries By Brian D. Davison, David G. Deschenes, and David B. Lewanda Proceedings of the Twelfth Int’l World Wide Web Conf., 2003.
The Compass Filter: Search Engine Result Personalization using Web Communities (pdf) By Apostolos Kritikopoulos and Martha Sideri Proceedings of Intelligent Techniques for Web Personalization ’03 (2003)
Stuff I’ve Seen: A System for Personal Information Retrieval and Re-Use (pdf) By Susan Dumais, Edward Cutrell, JJ Cadiz, Gavin Jancke, Raman Sarin, Daniel C. Robbins SIGIR’03, July 28 – August 1, 2003, Toronto, Canada.
Scaling Personalized Web Search By Glen Jeh and Jennifer Widom WWW2003, May 20-24, 2003, Budapest, Hungary.
An Analytical Comparison of Approaches to Personalizing PageRank (pdf) By Taher Haveliwala, Sepandar Kamvar and Glen Jeh Stanford Technical Report, June 2003
2004
The Perfect Search Engine Is Not Enough: A Study of Orienteering Behavior in Directed Search By Jaime Teevan, Christine Alvarado, Mark S. Ackerman, and David R. Karger CHI 2004, April 24–29, 2004, Vienna, Austria.
Personalizing Search Based on User Search Histories (pdf) By Mirco Speretta and Susan Gauch Submitted to CIKM ‘04.
A Community Aware Search Engine (pdf) By Rodrigo B. Almeida and Virgılio A. F. Almeida WWW2004, May 17–22, 2004, New York, New York, USA.
Understanding User Goals in Web Search (pdf) By Daniel E. Rose and Danny Levinson WWW 2004, May 17–22, 2004, New York, New York, USA.
Identifying Similarities, Periodicities, and Bursts for Online Search Queries (pdf) By Michail Vlachos, Chris Meek, and Zografoula Vagena Proceedings of ACM SIGMOD Conference, pages 131-142, 2004.
A Unified Approach to Personalization Based on Probabilistic Latent Semantic Models of Web Usage and Content (pdf) By Xin Jin, Yanzan Zhou, and Bamshad Mobasher AAAI Workshop on Semantic Web Personalization (SWP 2004)
Spying Out Real User Preferences for Metasearch Engine Personalization (pdf) By Lin Deng, Xiaoyong Chai, Qingzhao Tan, Wilfred Ng, and Dik Lun Lee Proceedings of the Sixth WebKDD Workshop: Webmining and Web Usage Analysis (WEBKDD ’04)
Web Usage Mining Based on Probabilistic Latent Semantic Analysis (pdf) By Xin Jin, Yanzan Zhou, Bamshad Mobasher Proceedings of the Sixth WebKDD Workshop: Webmining and Web Usage Analysis (WEBKDD ’04)
Personalized Web Search For Improving Retrieval Effectiveness (pdf) By Fang Liu, Clement Yu, Weiyi Meng IEEE Transactions on Knowledge and Data Engineering, VOL. 16, NO. 1, January 2004
PROS: A Personalized Ranking Platform for Web Search (pdf) 2004 By Paul-Alexandru Chirita, Daniel Olmedilla, and Wolfgang Nejdl
Adaptive Web Search Based on User Profile Constructed without Any Effort from Users (pdf) By Kazunari Sugiyama, Kenji Hatano, and Masatoshi Yoshikawa WWW2004, May 17–22, 2004, New York, New York, USA.
Personalizing PageRank Based on Domain Profiles By Filippo Menczer, Mehmet S. Aktas, and Mehmet A. Nacar (June 2004)
Using Hyperlink Features to Personalize Web Search (pdf) By Mehmet S. Aktas, Mehmet A. Nacar, and Filippo Menczer Proceedings of the 6th KDD International Workshop on Knowledge Discovery from the Web (WebKDD 2004). To appear as LNCS 3932, Springer
2005
The Re:Search Engine Helping People Return to Information on the Web By Jaime Teevan Proceedings of SIGIR ’05 (Doctoral Consortium).
Detecting Dominant Locations from Search Queries (pdf) By Lee Wang, Chuang Wang, Xing Xie, Josh Forman, Yansheng Lu, Wei-Ying Ma, and Ying Li SIGIR’05, August 15–19, 2005, Salvador, Brazil.
Web Resource Geographic Location Classification and Detection (pdf) By Chuang Wang, Xing Xie, Lee Wang, Yansheng Lu, and Wei-Ying Ma Proceedings of International World Wide Web conference, pages 1138-1139, 2005.
Personalized Ranking of Search Results with Learned User Interest Hierarchies from Bookmarks (pdf) By Hyoung-rae Kim and Philip K. Chan Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 21st, 2005, Chicago, Illinois, USA
Discovery of Significant Usage Patterns from Clusters of Clickstream Data (pdf) By Lin Lu, Margaret Dunham, and Yu Meng Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 21st, 2005, Chicago, Illinois, USA
Communities, Collaboration and Cooperation in Personalized Web Search (pdf) By Jill Freyne and Barry Smyth Proceedings of the Third Workshop on Intelligent Techniques for Web Personalization (ITWP ’05)
A Fuzzy Hybrid Collaborative Filtering Technique for Web Personalization (pdf) By Bhushan Shankar Suryavanshi, Nematollaah Shiri, and Sudhir P. Mudur Proceedings of the Third Workshop on Intelligent Techniques for Web Personalization (ITWP ’05)
Beyond the Commons: Investigating the Value of Personalizing Web Search (pdf) By Jaime Teevan, Susan T. Dumais, and Eric Horvitz PIA 2005 – Workshop on New Technologies for Personalized Information Access, July 24th and 25th, 2005, Edinburgh, Scotland, UK
A Meta Search Engine for User Adaptive Information Retrieval Interfaces for Desktop and Mobile Devices (pdf) Slides By Ernesto William De Luca and Andreas Nürnberger PIA 2005 – Workshop on New Technologies for Personalized Information Access, July 24th and 25th, 2005, Edinburgh, Scotland, UK
Using ODP Metadata to Personalize Search (pdf) By Paul-Alexandru Chirita, Wolfgang Nejdl, Raluca Paiu, and Christian Kohlschutter SIGIR 2005 Salvador, Brazil
Personalizing Search via Automated Analysis of Interests and Activities (pdf) By Jaime Teevan, Susan T. Dumais, and Eric Horvitz SIGIR ’05, August 15–19, 2005, Salvador, Brazil.
CubeSVD: A Novel Approach to Personalized Web Search (pdf) By Jian-Tao Sun, Hua-Jun Zeng, Huan Liu, Yuchang Lu, Zheng Chen WWW 2005, May 10-14, 2005, Chiba, Japan.
Analysis of User Web Traffic with a Focus on Search Activities (pdf) By Feng Qiu, Zhenyu Liu, Junghoo Cho Proceedings of the International Workshop on the Web and Databases (WebDB), June 2005.
Automatic Identification of User Goals in Web Search (pdf) By Uichin Lee, Zhenyu Liu, and Junghoo Cho Proceedings of the World-Wide Web Conference (WWW), May 2005.
2006
Automatic Identification of User Interest For Personalized Search By Feng Qiu and Junghoo Cho WWW 2006, May 23.26, 2006, Edinburgh, Scotland.
Time-Dependent Semantic Similarity Measure of Queries Using Historical Click-Through Data By Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, and Wei-Ying Ma WWW 2006, May 23.26, 2006, Edinburgh, Scotland.
Improving Personalized Web Search using Result Diversification (pdf) – By Filip Radlinski and Susan Dumais SIGIR’06, August 6–11, 2006, Seattle, Washington, USA.