KUMPOŠT, Marek. Data Preparation for User Profiling from Traffic Log. In Proceedings of The International Conference on Emerging Security Information, Systems, and Technologies (SECURWARE 2007). Los Alamitos, CA, USA: IEEE Computer Society. p. 89-94. ISBN 0-7695-2989-5. 2007.
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Basic information
Original name Data Preparation for User Profiling from Traffic Log
Name in Czech Příprava dat pro profilování
Authors KUMPOŠT, Marek (203 Czech Republic, guarantor).
Edition Los Alamitos, CA, USA, Proceedings of The International Conference on Emerging Security Information, Systems, and Technologies (SECURWARE 2007), p. 89-94, 6 pp. 2007.
Publisher IEEE Computer Society
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14330/07:00032428
Organization unit Faculty of Informatics
ISBN 0-7695-2989-5
Keywords in English user profiling; data mining; traffic log; privacy protection; user profiles
Tags data mining, privacy protection, traffic log, user profiles, user profiling
Tags International impact, Reviewed
Changed by Changed by: RNDr. Marek Kumpošt, Ph.D., učo 44545. Changed: 25/6/2009 11:29.
Abstract
User profiling is a technique that services use to provide customizable content to their users. These services operate with a user profile that reflects users' behaviour in the past. Profiling gives us some evidence about users' behaviour (information about their interests and social background). Instead of requiring users to state their interests, a service could learn this information from users' past activities. The main question is how much private information can be derived from context information that is related to an individual. The second question is to what extent a behaviour pattern can be used to pinpoint an individual among others.
Abstract (in Czech)
User profiling is a technique that services use to provide customizable content to their users. These services operate with a user profile that reflects users' behaviour in the past. Profiling gives us some evidence about users' behaviour (information about their interests and social background). Instead of requiring users to state their interests, a service could learn this information from users' past activities. The main question is how much private information can be derived from context information that is related to an individual. The second question is to what extent a behaviour pattern can be used to pinpoint an individual among others.
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