A data mining approach to library new book recommendations
In this paper, we propose a data mining approach to recommending new library books that have never been rated or borrowed by users. In our problem context, users are characterized by their demographic attributes, and concept hierarchies can be defined for some of these demographic attributes. Books...
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2002
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sg-smu-ink.sis_research-20352018-06-22T01:40:44Z A data mining approach to library new book recommendations HWANG, San-Yih LIM, Ee Peng In this paper, we propose a data mining approach to recommending new library books that have never been rated or borrowed by users. In our problem context, users are characterized by their demographic attributes, and concept hierarchies can be defined for some of these demographic attributes. Books are assigned to the base categories of a taxonomy. Our goal is therefore to identify the type of users interested in some specific type of books. We call such knowledge generalized profile association rules. In this paper, we propose a new definition of rule interestingness to prune away rules that are redundant and not useful in book recommendation. We have developed a new algorithm for efficiently discovering generalized profile association rules from a circulation database. It is noted that generalized profile association rules can be applied to other kinds of applications, including e-commerce. 2002-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1036 info:doi/10.1007/3-540-36227-4_23 https://ink.library.smu.edu.sg/context/sis_research/article/2035/viewcontent/Hwang_Lim2002_Chapter_ADataMiningApproachToNewLibrar.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems Numerical Analysis and Scientific Computing |
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Databases and Information Systems Numerical Analysis and Scientific Computing HWANG, San-Yih LIM, Ee Peng A data mining approach to library new book recommendations |
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In this paper, we propose a data mining approach to recommending new library books that have never been rated or borrowed by users. In our problem context, users are characterized by their demographic attributes, and concept hierarchies can be defined for some of these demographic attributes. Books are assigned to the base categories of a taxonomy. Our goal is therefore to identify the type of users interested in some specific type of books. We call such knowledge generalized profile association rules. In this paper, we propose a new definition of rule interestingness to prune away rules that are redundant and not useful in book recommendation. We have developed a new algorithm for efficiently discovering generalized profile association rules from a circulation database. It is noted that generalized profile association rules can be applied to other kinds of applications, including e-commerce. |
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HWANG, San-Yih LIM, Ee Peng |
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HWANG, San-Yih LIM, Ee Peng |
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HWANG, San-Yih |
title |
A data mining approach to library new book recommendations |
title_short |
A data mining approach to library new book recommendations |
title_full |
A data mining approach to library new book recommendations |
title_fullStr |
A data mining approach to library new book recommendations |
title_full_unstemmed |
A data mining approach to library new book recommendations |
title_sort |
data mining approach to library new book recommendations |
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Institutional Knowledge at Singapore Management University |
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2002 |
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https://ink.library.smu.edu.sg/sis_research/1036 https://ink.library.smu.edu.sg/context/sis_research/article/2035/viewcontent/Hwang_Lim2002_Chapter_ADataMiningApproachToNewLibrar.pdf |
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