[Objective] Through providing personalized book recommender service, enrich resource discovering methods and promote user awareness, book circulation under the situation of circulation decrease. [Methods] Using Apache Mahout, by normalizing circulation log data, using boolean user-based collaborative filtering recommendation with logarithm similarity algorithm, personalized book recommendations are generated and embedded in OPAC. [Results] Personalized book recommendations are embedded in OPAC, with automatic update every 10 days, and top 10 books are rendered to readers without recommendations. [Limitations] Lack of preference data, available recommenders are limited to boolean user-based recommenders. [Conclusions] The personalized book recommendation service receives attention and good fame. 7.5% readers click and read the recommendations, and about 3.1% borrow the recommended book.
刘丹. 利用Apache Mahout部署个性化图书推荐服务[J]. 现代图书情报技术, 2015, 31(10): 102-108.
Liu Dan. Personalized Book Recommender Service Deployment Using Apache Mahout. New Technology of Library and Information Service, 2015, 31(10): 102-108.
[1] 华东师范大学图书馆. 华东师范大学图书馆馆藏文献利用调查与分析[R/OL]. [2014-12-28]. http://www.lib.ecnu.edu. cn/about/lib_annual/.(East China Normal University Library. Investigation and Analysis on Utilization of the Holdings of East China Normal University Library [R/OL]. [2014-12-28]. http://www.lib.ecnu.edu.cn/about/lib_annual/.)
[2] 高凤荣, 马文峰, 王珊. 数字图书馆个性化信息推荐系统研究[J]. 情报理论与实践, 2003, 26(4): 359-362. (Gao Fengrong, Ma Wenfeng, Wang Shan. Research on Individual Information Recommendation System in Digital Library [J]. Information Studies: Theory & Application, 2003, 26(4): 359-362.)
[3] 王燕, 温有奎. 基于关联规则的推荐系统在数字图书馆中的应用[J]. 情报科学, 2007, 25(6): 877-880. (Wang Yan, Wen Youkui. The Applications of Recommendation System Based on Association Rules in the Digital Library [J]. Information Science, 2007, 25(6): 877-880.)
[4] 徐嘉莉, 陈佳. 一种快速的个性化书目推荐方法[J]. 现代图书情报技术, 2010(2): 79-84. (Xu Jiali, Chen Jia. A Fast Personalized Bibliographic Recommendation Method [J]. New Technology of Library and Information Service, 2010(2): 79-84.)
[5] 王代琳, 刘亚秋, 王真谛. 基于平均差异度的数字图书馆个性化推荐算法研究[J]. 图书情报工作, 2009, 53(11): 119-122. (Wang Dailin, Liu Yaqiu, Wang Zhendi. Personalized Recommendation Algorithm for Digital Library Based on Average Difference Degree [J]. Library and Information Service, 2009, 53(11): 119-122.)
[6] 赵麟. 基于最大频繁模式挖掘算法进行书目推荐系统的设计与实现[J]. 现代图书情报技术, 2010(5): 23-28. (Zhao Lin. The Design and Implementation of the Bibliographic Recommendation System Based on Maximal Frequent Patterns Mining Algorithm [J]. New Technology of Library and Information Service, 2010(5): 23-28.)
[7] 董坤. 基于协同过滤算法的高校图书馆图书推荐系统研究[J]. 现代图书情报技术, 2011(11): 44-47. (Dong Kun. Research of Personalized Book Recommender System of University Library Based on Collaborative Filter [J]. New Technology of Library and Information Service, 2011(11): 44-47.)
[8] 汪英姿. 基于本体的个性化图书推荐方法研究[J]. 现代图书情报技术, 2012(12): 72-78. (Wang Yingzi. Research on Ontology-based Personalized Recommendation Method for Library Resources [J]. New Technology of Library and Information Service, 2012(12): 72-78.)
[9] 张闪闪, 黄鹏. 高校图书馆图书推荐系统中的稀疏性问题实证探析[J]. 大学图书馆学报, 2014(6): 47-53. (Zhang Shanshan, Huang Peng. Empirical Study on Sparsity of University Libraries[J]. Journal of Academic Libraries, 2014(6): 47-53.)
[10] 王晓耘, 钱璐, 黄时友. 基于粗糙用户聚类的协同过滤推荐模型[J]. 现代图书情报技术, 2015(1): 45-51. (Wang Xiaoyun, Qian Lu, Huang Shiyou. Collaborative Filtering Recommendation Model Based on Rough User Clustering [J]. New Technology of Library and Information Service, 2015(1): 45-51.)
[11] 罗琳, 梁桂生, 蔡军. 基于分众分类法的图书馆书目推荐系统[J]. 现代图书情报技术, 2014(4): 14-19. (Luo Lin, Liang Guisheng, Cai Jun. Book Recommendation System Based on Folksonomy in Library [J]. New Technology of Library and Information Service, 2014(4): 14-19.)
[12] 奉国和, 黄家兴. 基于Hadoop与Mahout的协同过滤图书推荐研究[J]. 图书情报工作, 2013, 57(18): 116-121. (Feng Guohe, Huang Jiaxing. Research on Collaborative Filtering Book Recommendation Based on Hadoop and Mahout [J]. Library and Information Service, 2013, 57(18): 116-121.)
[13] Jannach D, Zanker M, Felfering A, 等. 推荐系统[M]. 蒋凡译. 北京: 人民邮电出版社, 2013: 2, 123. (Jannach D, Zanker M, Felfering A, et al. Recommender Systems [M]. Translated by Jiang Fan. Beijing: The People's Posts and Telecommunications Press, 2013: 2, 123.)
[14] Goldberg D, Nichols D, Oki B M, et al.Using Collaborative Filtering to Weave an Information Tapestry [J]. Communications of the ACM, 1992, 35(12): 61-70.
[15] 邱均平, 张聪. 高校图书馆馆藏资源协同推荐系统研究[J].图书情报工作, 2013, 57(22): 132-137.(Qiu Junping, Zhang Cong. Research on the Collaborative Recommendation System of University Library Resources [J]. Library and Information Service, 2013, 57(22): 132-137.)
[16] Owen S, Anil R, Dunning T, 等. Mahout实战[M]. 王斌, 韩冀中, 万吉译. 北京: 人民邮电出版社, 2014: 47. (Owen S, Anil R, Dunning T, et al. Mahout in Action[M].Translated by Wang Bin, Han Jizhong, Wan Ji. Beijing: The People's Posts and Telecommunications Press, 2014: 47.)
[17] What is Apache Mahout? [EB/OL]. [2015-06-30]. http://mahout.apache.org/.
[18] MovieLens [DB/OL]. [2015-06-30]. http://grouplens.org/datasets/movielens/.
