Title of article :
A Decision Theoretic Approach to Combining Information
Filters: An Analytical and Empirical Evaluation
Author/Authors :
Yuval Elovici and Bracha Shapira، نويسنده , , Paul B. Kantor، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2006
Abstract :
The outputs of several information filtering (IF) systems
can be combined to improve filtering performance. In
this article the authors propose and explore a framework
based on the so-called information structure (IS) model,
which is frequently used in Information Economics, for
combining the output of multiple IF systems according to
each user’s preferences (profile). The combination seeks
to maximize the expected payoff to that user. The authors
show analytically that the proposed framework increases
users expected payoff from the combined filtering output
for any user preferences. An experiment using the TREC-
6 test collection confirms the theoretical findings
Journal title :
Journal of the American Society for Information Science and Technology
Journal title :
Journal of the American Society for Information Science and Technology