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Research Article Open Access
Now a days web plays an important role in the distribution of information from different sources to the users. The main problem that comes into play is called Information overloading where, search engines retrieve plenty of contents related to any keyword query that are provided by the users. Users prefer the fast retrieval of data while browsing the portals. Here comes the importance of content recommendation. Content recommendation helps to overcome information overloading problem by choosing the best matching contents. Thus users get better response without wasting their time. Most of the recommendation systems face various difficulties while identifying high quality items and providing this to users. So this is our motivation for conducting an analysis on content recommendation. Here we compare different methods for content recommendation.