lactic 发表于 2025-3-28 18:33:46
Improving Rocchio Algorithm for Updating User Profile in Recommender Systems in the vector space model. Since in most content-based recommender systems, items and user profile are represented as vectors in a specific vector space, Rocchio algorithm is exploited for learning and updating user profile. In this paper we show how to improve the Rocchio algorithm by distinguishi破裂 发表于 2025-3-28 20:03:02
http://reply.papertrans.cn/103/10216/1021520/1021520_42.pngLucubrate 发表于 2025-3-28 23:30:04
Time-Aware Travel Attraction Recommendation the geo-related information to infer possible locations that tourists may be interested in. However, the temporal information, such as the date and time when the photo was taken, associated with these photos are not taken into account by most of existing works. We advocate that this information givCumulus 发表于 2025-3-29 05:58:52
http://reply.papertrans.cn/103/10216/1021520/1021520_44.pngoriginality 发表于 2025-3-29 10:44:00
http://reply.papertrans.cn/103/10216/1021520/1021520_45.pngmanifestation 发表于 2025-3-29 14:02:03
CGMF: Coupled Group-Based Matrix Factorization for Recommender Systemf the users that have close social relations with the given user. The underlying assumption is that a user’s taste is similar to his/her friends’ in social networking. In fact, users enjoy different groups of items with different preferences. A user may be treated as trustful by his/her friends moreTAP 发表于 2025-3-29 19:00:39
Authenticating Users of Recommender Systems Using Naive Bayes hold abundant personalized data that are valuable for KBA. This paper studies how to authenticate users with abundant rating data in recommender systems. For this, we propose a measurable user authentication scheme for recommender systems with secure personalized data under the Naive Bayes model. N蕨类 发表于 2025-3-29 22:19:25
http://reply.papertrans.cn/103/10216/1021520/1021520_48.png不愿 发表于 2025-3-30 01:12:32
Taxonomy Based Personalized News Recommendation: Novelty and Diversitynder systems have put their emphasis on the accuracy of finding the most similar items according to a user’s profile, while often ignoring other aspects that may affect users’ experiences in practice, e.g., the novelty and diversity issues within a recommendation list. In this paper, we focus on utiLipoma 发表于 2025-3-30 06:30:49
Taxonomy Based Personalized News Recommendation: Novelty and Diversitynder systems have put their emphasis on the accuracy of finding the most similar items according to a user’s profile, while often ignoring other aspects that may affect users’ experiences in practice, e.g., the novelty and diversity issues within a recommendation list. In this paper, we focus on uti