Tech Report: HPL-2007-72: Adaptive User Profiles for Enterprise Information Access

@techreport{citeulike:1300085, abstract = {A major challenge for users of enterprise information is finding the information they want, presented in a way that makes sense to them. In this paper we tackle this problem by creating adaptive user profiles from implicit behaviour. In traditional approaches to information filtering, the user has to explicitly create his or her profile, and manually keep the profile up to date. Taking advantage of the popularity of collaborative tagging systems, we use the recorded tagging behaviour to construct an implicit, yet realistic and dynamic user profile. We present and evaluate algorithms for creating such profiles, characterizing their behaviour through statistical analysis. In addition, we present a visualisation tool which was used in a small scale user study to provide insight as to the effectiveness of our approach. Finally, we show how the profiles can be leveraged to enable personalised access to enterprise data sources. Publication Info: WWW200716th International World Wide Web Conference, May 8-12 2007, Banff, Canada}, author = {Michlmayr, Elke and Cayzer, Steve and Shabajee, Paul }, citeulike-article-id = {1300085}, journal = {HP Labs Technical Reports}, keywords = {algorithms, clustering, enterprise, folksonomy, graphtheory, hp, networkdynamics, socialsoftware, tagging}, month = {May}, posted-at = {2007-07-16 18:10:33}, priority = {2}, publisher = {HP Labs}, title = {Tech Report: HPL-2007-72: Adaptive User Profiles for Enterprise Information Access}, url = {http://www.hpl.hp.com/techreports/2007/HPL-2007-72.html}, year = {2007} }

TY - RPRT ID - citeulike:1300085 L3 - citeulike-article-id:1300085 TI - Tech Report: HPL-2007-72: Adaptive User Profiles for Enterprise Information Access JF - HP Labs Technical Reports PB - HP Labs N2 - A major challenge for users of enterprise information is finding the information they want, presented in a way that makes sense to them. In this paper we tackle this problem by creating adaptive user profiles from implicit behaviour. In traditional approaches to information filtering, the user has to explicitly create his or her profile, and manually keep the profile up to date. Taking advantage of the popularity of collaborative tagging systems, we use the recorded tagging behaviour to construct an implicit, yet realistic and dynamic user profile. We present and evaluate algorithms for creating such profiles, characterizing their behaviour through statistical analysis. In addition, we present a visualisation tool which was used in a small scale user study to provide insight as to the effectiveness of our approach. Finally, we show how the profiles can be leveraged to enable personalised access to enterprise data sources. Publication Info: WWW200716th International World Wide Web Conference, May 8-12 2007, Banff, Canada KW - algorithms KW - clustering KW - enterprise KW - folksonomy KW - graphtheory KW - hp KW - networkdynamics KW - socialsoftware KW - tagging AU - Michlmayr, Elke AU - Cayzer, Steve AU - Shabajee, Paul PY - 2007/05/02/ UR - http://www.hpl.hp.com/techreports/2007/HPL-2007-72.html ER -