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traditional keyword based search, and provides recommendation that fits the user's personal preferences better. We demonstrate our method by applying it to product review recommendation based on user preferred composition style.
At present,the internet pornographic text is in varied forms and changeful, although it is prohibited ever. It severely harms people's mental and physical health development and social stability. There are IP-based,keyword-based and intelligent content analysis filtering system against it today. But they are difficult
This paper proposes a novel personalized news recommendation system named InfoSlim. The new system uses semantic technique to annotate news items and user preference in order to add rich metadata information into traditional keyword vector. By doing this, the similarity measure between item profile and user profile
This thesis studies a user interest model which can correspond with every user by collecting some personal information of users and optimize the retrieval results by search the original query expansion automatically. After putting the inquiry keyword into the search engine, the system will filter and sort the
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.