On Discovering Non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems

Panagiotis Adamopoulos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)
Original languageEnglish (US)
Title of host publication7th ACM Conference on Web Search and Data Mining
Subtitle of host publicationWSDM 2014
PublisherAssociation for Computing Machinery (ACM)
DOIs
StatePublished - 2014

Keywords

  • Recommender Systems

Cite this

Adamopoulos, P. (2014). On Discovering Non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems. In 7th ACM Conference on Web Search and Data Mining: WSDM 2014 Association for Computing Machinery (ACM). https://doi.org/10.1145/2556195.2556204

On Discovering Non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems. / Adamopoulos, Panagiotis.

7th ACM Conference on Web Search and Data Mining: WSDM 2014. Association for Computing Machinery (ACM), 2014.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Adamopoulos, P 2014, On Discovering Non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems. in 7th ACM Conference on Web Search and Data Mining: WSDM 2014. Association for Computing Machinery (ACM). https://doi.org/10.1145/2556195.2556204
Adamopoulos P. On Discovering Non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems. In 7th ACM Conference on Web Search and Data Mining: WSDM 2014. Association for Computing Machinery (ACM). 2014 https://doi.org/10.1145/2556195.2556204
Adamopoulos, Panagiotis. / On Discovering Non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems. 7th ACM Conference on Web Search and Data Mining: WSDM 2014. Association for Computing Machinery (ACM), 2014.
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