KNN-based clustering for improving social recommender systems

Publication Type:
Conference Proceeding
Citation:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 7607 LNAI pp. 115 - 125
Issue Date:
2013-02-04
Metrics:
Full metadata record
Files in This Item:
Filename Description Size
pangrong2.pdfPublished Version415.89 kB
Adobe PDF
Clustering is useful in tag based recommenders to reduce sparsity of data and by doing so to improve also accuracy of recommendation. Strategy for the selection of tags for clusters has an impact on the accuracy. In this paper we propose a KNN based approach for ranking tag neighbors for tag selection. We study the approach in comparison to several baselines by using two datasets in different domains. We show, that in both cases the approach outperforms the compared approaches. © 2013 Springer-Verlag.
Please use this identifier to cite or link to this item: