Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics

Paul Seitlinger, Dominik Kowald, Simone Kopeinik, Ilire Hasani-Mavriqi, Tobias Ley, Elisabeth Lex

Research output: Working paperPreprint

Abstract

Classic resource recommenders like Collaborative Filtering (CF) treat users as being just another entity, neglecting non-linear user-resource dynamics shaping attention and interpretation. In this paper, we propose a novel hybrid recommendation strategy that refines CF by capturing these dynamics. The evaluation results reveal that our approach substantially improves CF and, depending on the dataset, successfully competes with a computationally much more expensive Matrix Factorization variant.
Original languageEnglish
Publication statusPublished - 30 Jan 2015

Publication series

NamearXiv.org e-Print archive
PublisherCornell University Library

Keywords

  • recommender systems
  • ressource recommendations
  • cognitive science
  • algorithm

ASJC Scopus subject areas

  • General Computer Science

Fields of Expertise

  • Information, Communication & Computing

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