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An Experiment in Recommending Content from an Information Portal
Last modified: 2008-08-25
Abstract
There are manifold information sources producing new content offered through the Web. Information portals (especially those of information agencies) belong to most prolific sources - they produce new content seemingly continuously. On the other hand, they are typically not focused on a limited domain but cover a wide spectrum from actual events through sport and health to hobby and leisure time. As a result, user is naturally interested only in a portion of the produced content. He/she must filter out content in which he/she is not interested - and the filtering effort may decide whether he/she will return again or not. One possibility how to minimise the effort is to use a recommender system which is able to recommend user those published information pieces which match his/her interests. We have built a simple recommender on top of an information portal in order to experiment with it.
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