Using tag similarity in SVD-based recommendation systems
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 th...
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| creator | Osmanli, O. N. Toroslu, I. H. |
| description | 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. |
| doi_str_mv | 10.1109/ICAICT.2011.6111034 |
| format | Conference Proceeding |
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Our experiments illustrated that, tags increase the performance to some extent. The more similar tags means, the more accurate predictions.</description><subject>Java</subject><subject>Linear approximation</subject><subject>Matrix decomposition</subject><subject>Motion pictures</subject><subject>Ontologies</subject><subject>Recommendation Systems</subject><subject>Recommender systems</subject><subject>Singular value decomposition</subject><subject>Tag Similarity</subject><isbn>1612848311</isbn><isbn>9781612848310</isbn><isbn>9781612848303</isbn><isbn>1612848303</isbn><isbn>161284832X</isbn><isbn>9781612848327</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1j81OwzAQhI0QElDyBL34BRK8tpPYRxR-WqkSB9Jeq3W8royaFMW55O2JRJnLaL7DaIaxNYgCQNjnbfOybdpCCoCiggUpfcMyWxuoQBptlFC37PE_ANyzLKVvsaiStdH2gZl9isOJT3jiKfbxjGOcZh4H_nV4zR0m8nyk7tL3NHic4mXgaU4T9emJ3QU8J8quvmLt-1vbbPLd58cya5dHK6Y8aBPIlwjBlVrKOpDwAdBKi52jWqFUPhhZ6s4ZQmlQVZqCRy2dckqVasXWf7WRiI4_Y-xxnI_Xr-oXjbtIrQ</recordid><startdate>201110</startdate><enddate>201110</enddate><creator>Osmanli, O. 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N.</creatorcontrib><creatorcontrib>Toroslu, I. H.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Osmanli, O. N.</au><au>Toroslu, I. 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| ispartof | 2011 5th International Conference on Application of Information and Communication Technologies (AICT), 2011, p.1-4 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Java Linear approximation Matrix decomposition Motion pictures Ontologies Recommendation Systems Recommender systems Singular value decomposition Tag Similarity |
| title | Using tag similarity in SVD-based recommendation systems |
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