Content-Based News Recommendation
نویسندگان
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 web and 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 the 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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