Department of Computer Engineering
S E M I N A R
Efficiency and Effectiveness of Cluster Based Collaborative Filtering Using Inverted Indexing
Ozlem Nurcan Subakan
Collaborative filtering is a relatively new technique for information filtering which has been successfully used in domains where the information content is not easily parse-able and traditional information filtering techniques are difficult to apply. Collaborative filtering works over a database of ratings for items by users. A crucial issue for a collaborative filtering based system is the accuracy and time efficiency. In order to reduce the memory cost of collaborative filtering we propose to exploit inverted indexing structures stored on disk. We will combine collaborative filtering and content based approaches to solve cold start and new item problems and compare the efficiency and effectiveness of the proposed system with the existing techniques.
DATE: April 4, 2005, Monday @ 16:40
PLACE: EA 409