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In this study, we propose VSRank, a novel framework that seeks accuracy improvement of ranking-based CF through adaptation of the vector space model. ... Collaborative filtering (CF) is an effective technique addressing the information overload problem. CF approaches generally fall into two categories: rating-based and ranking-based. ... THE VSRANK FRAMEWORK In this section, we present VSRank, a novel framework for adapting vector space model to rankingbased collaborative filtering (CF). ...doi:10.1145/2542048 fatcat:b3qynid4ivdcpmf5z5xjlylxqa
Collaborative filtering (CF) is an effective technique addressing the information overload problem. ... We then use a novel degree-specialty weighting scheme resembling TF-IDF to weight the terms. ... Collaborative filtering. The two main paradigms for recommender systems are content-based filtering and collaborative filtering (CF). ...doi:10.1145/2396761.2398458 dblp:conf/cikm/WangSGM12 fatcat:tcnhgldkdbg5nchzmyksjx2f74
Unlike many other domains, this approach has not achieved a desired performance in collaborative filtering problems, probably due to unavailability of appropriate textual data. ... It uses the concept of profile co-occurrence for defining relations among entities and applies a factorization method for embedding the users and items. ... GEMRANK In this section we introduce GEMRank, that is a framework for embedding users and items in a collaborative filtering task and use their vector representations for like/dislike prediction. ...arXiv:1811.01686v1 fatcat:mlyglao7qrfv3huunoym5hodtu
In this paper, we propose a novel graph-based approach, called GRank, that is designed for collaborative ranking domain. ... Data sparsity, that is a common problem in neighbor-based collaborative filtering domain, usually complicates the process of item recommendation. ... Collaborative ranking Collaborative ranking is a class of collaborative filtering algorithms that seeks to predict how a user will rank items. ...doi:10.1016/j.eswa.2016.09.013 fatcat:c5pxcfm2inadnkwl6nyclyf6me
This article presents a novel framework, called IteRank, that models the data as a bipartite network containing users and pairwise preferences. ... Neighbor-based collaborative ranking (NCR) techniques follow three consecutive steps to recommend items to each target user: first they calculate the similarities among users, then they estimate concordance ... This paper seeks to propose a novel framework that significantly improves the performance of the current neighbor-based collaborative ranking methods. ...arXiv:1811.01345v1 fatcat:hajb7zitzjawjbdvjldiasymky