From x-rays to silly putty via Uranus: serendipity and its role in web search

The act of encountering information unexpectedly has long been identified as valuable, both as a joy in itself and as part of task-focused problem solving. There has been a concern that highly accurate search engines and targeted personalization may reduce opportunities for serendipity on the Web. We examine whether there is the potential for serendipitous encounters during Web search, and whether improving search relevance through personalization reduces this potential. By studying Web search query logs and the results people judge relevant and interesting, we find many of the queries people perform return interesting (potentially serendipitous) results that are not directly relevant. Rather than harming serendipity, personalization appears to identify interesting results in addition to relevant ones.

[1]  P. Andel.  Anatomy of the Unsought Finding. Serendipity: Orgin, History, Domains, Traditions, Appearances, Patterns and Programmability , 1994, The British Journal for the Philosophy of Science.

[2]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[3]  Oscar de Bruijn,et al.  A New Framework for Theory-Based Interaction Design Applied to Serendipitous Information Retrieval , 2008, TCHI.

[4]  Nigel Ford,et al.  Serendipity and information seeking: an empirical study , 2003, J. Documentation.

[5]  Amanda Spink,et al.  From Highly Relevant to Not Relevant: Examining Different Regions of Relevance , 1998, Inf. Process. Manag..

[6]  Susan T. Dumais,et al.  Personalizing Search via Automated Analysis of Interests and Activities , 2005, SIGIR.

[7]  ChengXiang Zhai,et al.  Implicit user modeling for personalized search , 2005, CIKM '05.

[8]  Sanda Erdelez,et al.  Investigation of information encountering in the controlled research environment , 2004, Inf. Process. Manag..

[9]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[10]  Sean M. McNee,et al.  Improving recommendation lists through topic diversification , 2005, WWW '05.

[11]  Peter W. Foltz,et al.  Learning from text: Matching readers and texts by latent semantic analysis , 1998 .

[12]  Sandra Erdelez.  Information Encountering: It's More Than Just Bumping into Information , 2005 .

[13]  Susan T. Dumais,et al.  Beyond the Commons: Investigating the Value of Personalizing Web Search , 2005 .

[14]  ErdelezSanda.  Investigation of information encountering in the controlled research environment , 2004 .