PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Miha Grcar
In: SIKDD 2004 at multiconference IS 2004, 12-15 Oct 2004, Ljubljana, Slovenia.


Collaborative filtering is based on the assumption that “similar users have similar preferences”. In other words, by finding users that are similar to the active user and by examining their preferences, the recommender system can (i) predict the active user’s preferences for certain items and (ii) provide a ranked list of items which active user will most probably like. Collaborative filtering generally ignores the form and the content of the items and can therefore also be applied to non-textual items. Furthermore, collaborative filtering can detect relationships between items that have no content similarities but are linked implicitly through the groups of users accessing them. These groups (communities) are formed around a specific user profile.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:User Modelling for Computer Human Interaction
Information Retrieval & Textual Information Access
ID Code:740
Deposited By:Blaz Fortuna
Deposited On:30 December 2004