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Research of Books Recommendation of Borrow Preference Uncertainty in University Readers Based on Cloud Model and Multi-feature |
Li Kechao, Lan Dongmei, Ling Xiaoe |
Library of Guangxi Normal University for Nationalities, Chongzuo 532200, China |
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Abstract The paper, taking advantages of cloud model in expressing uncertainty of fuzziness and randomness in nature, proposes that there are uncertainties in cloud model and readers’ multi-featured books preference.The paper computes the weighted similarity of readers’ majors, genders and grades,uses the backward cloud algorithm to compute readers’ preference of borrow-return time interval that is expressed in cloud expectation, entropy and hyper entropy,and then computes the readers’ cloud similarity. Combining multi-featured similarity of readers with cloud similarity,the paper finally recommends books to readers with copied ones and proves the validity of the algorithm by experiments.
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Received: 18 February 2013
Published: 03 July 2013
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