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VSRank

Shuaiqiang Wang, Jiankai Sun, Byron J. Gao, Jun Ma
2014 ACM Transactions on Intelligent Systems and Technology  
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

Adapting vector space model to ranking-based collaborative filtering

Shuaiqiang Wang, Jiankai Sun, Byron J. Gao, Jun Ma
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
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

GEMRank: Global Entity Embedding For Collaborative Filtering [article]

Arash Khoeini, Bita Shams, Saman Haratizadeh
2018 arXiv   pre-print
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

Graph-based collaborative ranking

Bita Shams, Saman Haratizadeh
2017 Expert systems with applications  
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

IteRank: An iterative network-oriented approach to neighbor-based collaborative ranking [article]

Bita Shams, Saman Haratizadeh
2018 arXiv   pre-print
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