Local Popularity and Time in top-N Recommendation

Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Azzurra Ragone, Joseph Trotta
7/11/2018
cs.IR

Official code: sisinflab/recommenders (8 stars, Apache-2.0, last commit 2019-03-08). 1 more implementation below.

Abstract

Items popularity is a strong signal in recommendation algorithms. It strongly affects collaborative filtering approaches and it has been proven to be a very good baseline in terms of results accuracy. Even though we miss an actual personalization, global popularity can be effectively used to recommend items to users. In this paper we introduce the idea of a time-aware personalized popularity in recommender systems by considering both items popularity among neighbors and how it changes over time. An experimental evaluation shows a highly competitive behavior of the proposed approach, compared to state of the art model-based collaborative approaches, in terms of results accuracy.

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Code Implementations(2)

sisinflab/recommendersOfficial100%
Apache-2.0

Recommender Systems algorithms implementations

82Java, KotlinJul 20, 20187 years agoApache-2.0
sisinflab/DatasetsSplitsOfficial100%
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This is a collection of splittings of publicly available Datasets. This collection has been created for two main purposes:

32JavaJan 5, 20187 years agoApache-2.0

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Cite this paper

@article{anelli2018local,
  title  = {Local Popularity and Time in top-N Recommendation},
  author = {Vito Walter Anelli and Tommaso Di Noia and Eugenio Di Sciascio and Azzurra Ragone and Joseph Trotta},
  year   = {2018},
  eprint = {1807.04204},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1807.04204}
}

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