Titlebook: Web Information Systems Engineering -- WISE 2013; 14th International C Xuemin Lin,Yannis Manolopoulos,Guangyan Huang Conference proceedings

lactic

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

Lucubrate

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 giv

Cumulus

originality

manifestation

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 more

TAP

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

蕨類

不愿

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

Lipoma

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