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Summary: An Intelligent Knowledge Sharing Strategy Featuring Item-Based
Collaborative Filtering and Case Based Reasoning
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 propose a new approach for
combining item-based Collaborative Filtering (CF)
with Case Based Reasoning (CBR) to pursue
personalized information filtering in a knowledge
sharing context. Functionally, our personalized
information filtering approach allows the use of
recommendations by peers with similar interests and
domain experts to guide the selection of information
deemed relevant to an active user's profile. We apply
item-based similarity computation in a CF framework
to retrieve N information objects based on the user's
interests and recommended by peer. The N information
objects are then subjected to a CBR based
compositional adaptation method to further select
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