Movie recommendations based in explicit and implicit features extracted from the Filmtipset dataset

Fernando Díez,J. Enrique Chavarriaga,Pedro G. Campos,Alejandro Bellogín

CAMRa '10: Proceedings of the Workshop on Context-Aware Movie Recommendation（2010）

引用 20|浏览0

暂无评分

摘要

In this paper, we describe the experiments conducted by the Information Retrieval Group at the Universidad Autónoma de Madrid (Spain) in order to better recommend movies for the 2010 CAMRa Challenge edition. Experiments were carried out on the dataset corresponding to social Filmtipset track. To obtain the movies recommendations we have used different algorithms based on Random Walks, which are well documented in the literature of collaborative recommendation. We have also included a new proposal in one of the algorithms in order to get better results. The results obtained have been computed by means of the trec_eval standard NIST evaluation procedure.

查看译文

关键词

different algorithm,movie recommendations,social filmtipset track,information retrieval group,random walks,social networks,universidad aut,filmtipset dataset,movie recommendation,random walk,collaborative recommendation,challenge,recommender systems,camra challenge edition,better result,implicit feature,new proposal,movies recommendation,information retrieval,feature extraction,recommender system,social network

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要