A recommendation system can be trained using user intent and context. Such user intent can be determined using a user history of interaction with an analytics system. The user history can either be that of the user accessing the recommendation system or an exemplary user history to broaden the ...
long-term user profiles and short-term sequential patterns from sessions can lead to more accurate models known as the session-aware recommendation methods... MP Tu,TC Thanh,NX Bach - 《IEEE Access》 被引量: 0发表: 2019年 A Multi-Period Product Recommender System in Online Food Market based...
[1]L. Baltrunas and F. Ricci. Experimental evaluation of context-dependent collaborative filtering using item splitting.2013. [2]Yong Zheng,Robin Burke,Bamshad Mobasher.Splitting Approaches for Context-Aware Recommendation: An Empirical Study.2014...
Citation recommendation aims to help authors in selecting the most relevant papers to cite from a potentially overwhelming number of references. In this pa... Rokach,Mitra,Kataria 被引量: 22发表: 2013年 Context-Aware Scenarios for Pervasive Long-Life Learning In the p-LearNet project, we are ...
As a class of context-aware systems, context-aware service recommendation aims to bind high-quality services to users while taking into account their context requirements, including invocation time, location, social profiles, connectivity, and so on. However, current CASR approaches are not scalable...
Because the existing recommendation system performs the recommendation by using the information directly input by users and application usage record only, it is not possible to reflect the context information generated in u-healthcare environments. This study develops a item context-aware model using ...
CONTEXT AWARE RECOMMENDATION In accordance with aspects of the disclosure, systems and methods are provided for managing context aware recommendations by providing recommendations to a... Li, Wen-syan,Shi, Xingtian - ACM 被引量: 2发表: 2015年 DCARS: Deep context-aware recommendation system based...
In this respect, the key challenge is how to realize personalized course recommendation as well as to reduce the computing and storage costs for the tremendous course data. In this paper, we propose a big data-supported, context-aware online learning-based course recommender system that could ...
Due to the influence of context information on user behavior, context-aware recommendation system (CARS) has attracted extensive attention in recent years. The most advanced context-aware recommendation system maps the original multi-field features into a shared hidden space and then simply connects it...
In this work, we propose a privacy-preserving method for the context-aware recommendation system in the two-cloud model. In particular, we first adjust the standard additive secret sharing scheme to support secure negative integers computation, based on which we manage to design secure comparison ...