- Autor
- Lacic, Emanuel
- Kowald, Dominik
- Lex, Elisabeth
- TitelNeighborhood Troubles
- On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations
- Datei
- Persistent Identifier
- Erschienen inEntity Retrieval Workshop @ ACM CIKM 2018 Conference
- Erscheinungsjahr2018
- LicenceCC-BY
- Download Statistik1461
- Peer ReviewJa
- Abstract 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 evaluated our approach on a dataset gathered from Foursquare and our evaluation results suggest that our proposed user pre-filtering step can help to achieve both a better runtime performance as well as an increase in overall recommendation accuracy.
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