Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Case Based Reasoning for Information Personalization: Using a Context-Sensitive
 

Summary: Case Based Reasoning for Information
Personalization: Using a Context-Sensitive
Compositional Case Adaptation Approach
Zeina Chedrawy and Syed Sibte Raza Abidi
Faculty of Computer Science, Dalhousie University, Halifax B3H 1W5,Canada
{chedrawy,sraza}@cs.dal.ca
Abstract-In this paper, we present an intelligent information
filtering strategy that is a hybrid of item-based Collaborative
Filtering (CF) and Case Based Reasoning (CBR) methods.
Information filtering is implemented in two phases: in phase I, we
have developed a multi-feature item-based CF strategy that
allows creating a detailed context for filtering the information
and retrieving N information objects based on user's interests and
also preferred by similar users with similar tastes. In phase II, we
use the N retrieved items as input to the CBR information
filtering system and apply CBR-based compositional adaptation
technique to selectively collect distinct information components of
the N retrieved past items pairs to produce a composite
recommendation that better addresses the initial user's interests
and needs. We show that the hybrid of context-based similarity

  

Source: Abidi, Syed Sibte Raza - Faculty of Computer Science, Dalhousie University

 

Collections: Computer Technologies and Information Sciences