| Today with the rapid development of the Internet,although the user can quickly and easily access the information,but in the face of a large number of information content,users still cannot be accurate in a short time to obtain the desired target information,resulting in a great time and energy waste.In the development and operation of BanMa Bang Sports News website,in order to facilitate football fans access to the football information which they interested in timely,reduce the time that users search on and improve the experience of the users' news reading,increase user's stickiness to the website,this paper designs and implements the Ban Ma Bang Sports News website based on the collaborative filtering algorithm of the items Personalized recommendation system.In this paper,according to the list page display,user browsing history data collection and data analysis and other five functional modules division,basing on the TF-IDF technology to design and implement the BanMa Bang website personalized news recommendation for specific users.Aiming at the problem of "cold start" and "data sparsity",this paper also proposes a solution to recommend popular news and expand the search scope of similar news.The recommendation system in this paper improves the accuracy of BanMa Bang Sports News recommendation system and users' satisfaction,solving the problem of information overload and disorientation caused by the excessive amount of BanMaBang Sports News better. |
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