Collecting Data for the Profiling of Web Users

Internet technology allows web site administrators to monitor users visiting their sites. In the beginning the basic protocol used for the web (http) did not consider the concept of a session. It was impossible to recognise whether two requests came from the same user. Developers then found ways to follow visitors and implemented logins and shopping carts. These solutions included cookie session IDs encoded in the URL, or more recently the creation of a virtual host for each visitor. These mechanisms have also been used for statistical purposes, to study the behaviour of groups of users (group profiling) and to predict the behaviour of a specific user (user profiling). Usually, collecting information is not in itself reprehensible; however, the use of the data is more critical. One can never be sure if it will be used for statistics (on anonymised data), for one-to-one marketing, or be sold to a third party. The W3 Consortium has published a standard called P3P, giving web site administrators the possibility to declare their policy regarding privacy in a machine readable format. Unfortunately, most people are not yet aware of the sensitivity of collected data; there is therefore no wide resistance to the creation of huge interoperable databases.

[1]  Elisa Bertino,et al.  A Framework for Evaluating Privacy Preserving Data Mining Algorithms* , 2005, Data Mining and Knowledge Discovery.

[2]  Sadie Plant Zeros + ones : digital women + the new technoculture , 1997 .

[3]  Michael J. A. Berry,et al.  Mastering Data Mining: The Art and Science of Customer Relationship Management , 1999 .

[4]  Jaideep Srivastava,et al.  Web usage mining: discovery and applications of usage patterns from Web data , 2000, SKDD.

[5]  Myra Spiliopoulou,et al.  Web Usage Analysis and User Profiling , 2002, Lecture Notes in Computer Science.

[6]  Lorrie Faith Cranor,et al.  I Didn't buy It for Myself , 2004, Designing Personalized User Experiences in eCommerce.

[7]  John Riedl Guest Editor's Introduction: Personalization and Privacy , 2001, IEEE Internet Comput..

[8]  Simson L. Garfinkel,et al.  Web Security, Privacy and Commerce , 2001 .

[9]  Yanchun Zhang,et al.  Towards User Profiling for Web Recommendation , 2005, Australian Conference on Artificial Intelligence.

[10]  Maria Madlberger,et al.  Evaluating personalization and customization from an ethical point of view: an empirical study , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[11]  Myra Spiliopoulou,et al.  Web Usage Analysis and User Profiling: International WEBKDD'99 Workshop San Diego, CA, USA, August 15, 1999 Revised Papers , 2000 .

[12]  Won Kim,et al.  Personalization: Definition, Status, and Challenges Ahead , 2002, J. Object Technol..

[13]  M. Poster The Second Media Age , 1994 .

[14]  Mireille Hildebrandt Profiling: From data to knowledge , 2006, Datenschutz und Datensicherheit - DuD.

[15]  Lorrie Faith Cranor,et al.  'I didn't buy it for myself' privacy and ecommerce personalization , 2003, WPES '03.

[16]  Nikhilesh Dholakia,et al.  Privacy and Consumer Agency in the Information Age: Between Prying Profilers and Preening Webcams , 2005 .

[17]  P. Agre,et al.  Technology and privacy: The new landscape , 1998 .

[18]  Analía Amandi,et al.  User profiling for Web page filtering , 2005, IEEE Internet Computing.

[19]  BertinoElisa,et al.  A Framework for Evaluating Privacy Preserving Data Mining Algorithms , 2005 .

[20]  Hyung Joon Kook,et al.  Profiling Multiple Domains of User Interests and Using Them for Personalized Web Support , 2005, ICIC.

[21]  Jaideep Srivastava,et al.  Automatic personalization based on Web usage mining , 2000, CACM.

[22]  D. Zwick,et al.  Whose Identity Is It Anyway? Consumer Representation in the Age of Database Marketing , 2004 .

[23]  Jozsef Kovacs,et al.  Whose Identity Is It Anyway? , 2009, The American journal of bioethics : AJOB.

[24]  S. Garfinkel,et al.  Web Security, Privacy & Commerce , 2001 .