Publication | Closed Access
Recommender systems challenge 2014
31
Citations
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References
2014
Year
Unknown Venue
Artificial IntelligenceEngineeringMachine LearningCommon GoalCommunicationJournalismText MiningComputational Social ScienceSocial MediaInformation RetrievalData ScienceData MiningContent AnalysisUser Behavior ModelingNew DatasetPredictive AnalyticsKnowledge DiscoveryConversational Recommender SystemComputer ScienceCold-start ProblemGroup RecommendersSocial ComputingInteractive MarketingArtsCollaborative FilteringMovie Ratings
The 2014 ACM Recommender Systems Challenge invited researchers and practitioners to work towards a common goal, this goal being the prediction of users engagement in movie ratings expressed on Twitter. More than 200 participants sought to join the challenge and work on the new dataset released in its scope. The participants were asked to develop new algorithms to predict user engagement and evaluate them in a common setting, ensuring that the comparison was objective and unbiased, within the challenge.
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