@inproceedings{f276f4db84be4e708afd972450c82a1a,
title = "Recommendation strategy using expanded neighbor collaborative filtering",
abstract = "The evaluation of recommender system is often biased towards accuracy, which is hard to balance all participants' interests. In this paper, a novel recommendation strategy using expanded neighbor collaborative filtering (ECF) is presented. Different from the standard collaborative filtering (CF), this recommendation strategy takes into account the second-order neighbors, which are expected to contribute to the coverage and diversity of recommendation. A transferring similarity is proposed to link the given user with second-order neighbors via nearest neighbors. Based on MovieLens dataset, the strategy was test on several typical similarity indexes. The numerical results confirmed the improvements on coverage and diversity compared to the benchmark CF, without affecting accuracy obviously.",
keywords = "Collaborative Filtering, Coverage, Diversity, Recommender System, Second-Order Neighbor",
author = "Bin Wang and Qi Gao and Xiaoxue Feng and Feng Pan",
note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",
year = "2017",
month = sep,
day = "7",
doi = "10.23919/ChiCC.2017.8027555",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "1451--1455",
editor = "Tao Liu and Qianchuan Zhao",
booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",
address = "United States",
}