An Improved Recommender System Based on Forgetting Mechanism for User Interest-Drifting
سال انتشار: 1391
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 202
فایل این مقاله در 9 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_ITRC-4-4_007
تاریخ نمایه سازی: 22 فروردین 1401
چکیده مقاله:
Highly effective recommender systems may still face users’ interest drifting. One of the main strategies for handling interest-drifting is forgetting mechanism. Current approaches based on forgetting mechanism have some drawbacks: (i) Drifting times are not considered to be detected in user interest over time. (ii) They are not adaptive to the evolving nature of user’s interest. Until now, there hasn’t been any study to overcome these problems. This paper discusses the above drawbacks and presents a novel recommender system, named WmIDForg, using web usage mining, web content mining techniques, and forgetting mechanism to address user interest-drift problem. We try to detect evolving and time-variant patterns of users' interest individually, and then dynamically use this information to predict favorite items of the user better over time. The experimental results on EachMovie dataset demonstrate our methodology increases recommendations precision ۶.۸۰% and ۱.۴۲% in comparison with available approaches with and without interest-drifting respectively.
کلیدواژه ها: