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Using tag similarity in SVD-based recommendation systems
Date
2011-12-01
Author
Osmanli, Osman Nuri
Toroslu, İsmail Hakkı
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Data analysis has become a very important area for both companies and researchers as a consequence of the technological developments in recent years. Companies are trying to increase their profit by analyzing the existing data about their customers and making decisions for the future according to the results of these analyses. Parallel to the need of companies, researchers are investigating different methodologies to analyze data more accurately with high performance. In this paper, we adopted free-formatted text-based tags into traditional 2-Dimensional SVD approach. We analysed the effect of different tag similarity techniques to the 3-Dimensional SVD recommendation performance. Our experiments illustrated that, tags increase the performance to some extent. The more similar tags means, the more accurate predictions. © 2011 IEEE.
Subject Keywords
Recommendation systems
,
Singular value decomposition
,
Tag similarity
URI
https://hdl.handle.net/11511/57871
DOI
https://doi.org/10.1109/icaict.2011.6111034
Collections
Department of Computer Engineering, Conference / Seminar