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The amount of information on the Web is rapidly increasing. Recommender systems can help users selectively filter this information based on their preferences. One way to obtain user preferences is to analyze characteristics of content that is accessed by the user. Unfortunately, web pages may contain elements irrelevant to user interests (e.g., navigation bar, advertisements, and links.). Hence, existing...
An amount of information on the Web has been increased explosively with the growth of information technology. In the area of electronic commerce, the recommender systems that provide personalized content are crucial research issue. The analysis of efficient user preference is important for improving the recommendation accuracy. Existing recommendation system has used implicit feedback for analyzing...
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.