You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Clustering and Case-Based Reasoning for User Stereotypes

Fulltext:


Publication Type:

Licentiate Thesis

Publisher:

Mälardalen University Press


Abstract

A user stereotype represents a certain kind of user who exhibits a set of specific characteristics - an abstraction of a group of similar users. Looking at statistical data gathered from a population of users, these groups can be identified either manually or using automated clustering %%@ techniques, and constructed by generalizing the most significant features of the identified groups. Case-Based Reasoning (CBR) is an Artificial %%@ Intelligence (AI) method based on the idea of reusing past experience in a domain-specific library of problem-solution descriptions, known as cases. %%@ By representing a solution to the problem of supplying a typical kind of user with appropriate information, it is natural to see user stereotype cases %%@ as part of a CBR process. This thesis describes the usage and creation of user stereotypes in novel domains, aided by the use of clustering %%@ techniques. The first application domain is personalization on the World Wide Web (WWW), where user stereotypes and a filtering technique called %%@ category-based filtering are combined to handle a frequently occurring problem on WWW sites attempting to automatically recommend items of interest to %%@ site visitors. In the second application domain, psychophysiological medicine, clustering is utilized to identify recurring patterns of previously classified time-series of Respiratory Sinus Arrhythmia (RSA). Using a combination of expert knowledge and repeated clustering, the aim %%@ is to incrementally build a case library of stereotypes which can be used in a CBR system for automated classification of RSA sequences.

Bibtex

@misc{Sollenborn644,
author = {Mikael Sollenborn},
title = {Clustering and Case-Based Reasoning for User Stereotypes},
number = {35},
month = {October},
year = {2004},
publisher = {M{\"a}lardalen University Press},
url = {http://www.es.mdh.se/publications/644-}
}