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Simulations for novel problems in recommendation: analyzing\n misinformation and data characteristics

  • arXiv (Cornell University)
  • Cornell University
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Abstract

In this position paper, we discuss recent applications of simulation\napproaches for recommender systems tasks. In particular, we describe how they\nwere used to analyze the problem of misinformation spreading and understand\nwhich data characteristics affect the performance of recommendation algorithms\nmore significantly. We also present potential lines of future work where\nsimulation methods could advance the work in the recommendation community.\n

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DOI
10.48550/arxiv.2110.04037
OpenAlex
W4298202917
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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