Slovenská Technická Univerzita V Bratislave Fakulta Informatiky a Informačných Technológií
نویسنده
چکیده
The information overloading is one of the biggest problems nowadays. We can see it in various domains, including business, especially in the news. This is more significant in connection to news portals, where the quality of the news portal is commonly measured by amount of news added to the site. Then the most renowned news portals add hundreds of new articles daily. The classical solution usually used to solve information overloading is a recommendation. In this paper we present an approach for fast content-based news recommendation, based on cosine-similarity search.
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تاریخ انتشار 2010