Cluster-based contextual recommendations
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Date
2016
Authors
Volume
2016
Issue
März
Journal
Advances in Database Technology - EDBT 2016-March (2016)
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Publisher
Konstanz : OpenProceedings.org
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Abstract
In this work, we address the problem of contextual recommendations by exploiting the concept of subspace clustering. Specifically, we pre-partition users that have rated subsets of data items similarly into clusters and we associate a context situation with each cluster. The cluster context is defined as any internally stored information that can be used to characterize the cluster members per se. Then, given a query context, we identify the clusters with the most similar context, and we use their members for making suggestions in a collaborative filtering manner. © 2016, Copyright is with the authors.
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CC BY-NC-ND 4.0 Unported