• Corpus ID: 52051965

Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations

@article{Laci2018NeighborhoodTO,
  title={Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations},
  author={Emanuel Laci{\'c} and Dominik Kowald and E. Lex},
  journal={ArXiv},
  year={2018},
  volume={abs/1808.06417}
}
In this paper, we present work-in-progress on applying user pre-filtering to speed up and enhance recommendations based on Collaborative Filtering. We propose to pre-filter users in order to extract a smaller set of candidate neighbors, who exhibit a high number of overlapping entities and to compute the final user similarities based on this set. To realize this, we exploit features of the high-performance search engine Apache Solr and integrate them into a scalable recommender system. We have… 

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