Abstract
A recent surge of subscriptions to online news
services exemplifies the fact that people and
organizations constantly need up-to-date information to
stay competitive and make better informed decisions.
However, many of these news services often require
users to either manually input their profiles or
subscribe to existing news channel. This results in
lack of intelligence and personalization, and thus make
them less attractive to users. In this paper, an
integrated model that combines query expansion with
ranking function adaptation for online information
routing is proposed and tested using two different
large scale corpora. The experimental results show that
this new model can deliver much better quality
information than existing models.
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