期刊文献+

基于聚类分析的大众点评餐馆评分结果分析 被引量:2

下载PDF
导出
摘要 一维聚类:合并大众点评三项餐馆评分数据进行聚类分析,分析结果为用户被分为两类;二维聚类:选取其中一类用户对每一项评分单独进行聚类分析,发现三项评分用户均被分为两类。其中聚类分析的具体方法为Two Step聚类和K-means聚类算法。
出处 《电子技术与软件工程》 2016年第17期159-160,共2页 ELECTRONIC TECHNOLOGY & SOFTWARE ENGINEERING
  • 相关文献

参考文献6

  • 1Cheng, Weijie, et al."CollaborativeFiltering Recommendation on Osers' Interest Sequences."PloS one 11.5 (2016):e0155739.
  • 2Melville, Prem, Raymond J.Mooney, and Ramadass Nagarajan."Content-boosted collaborative filtering for improved recommendations."Aaai/iaai. 2002.
  • 3胡必云,李舟军,王君,巢文涵.评分偏差对于推荐质量的影响[J].北京航空航天大学学报,2012,38(6):823-828. 被引量:3
  • 4未知.第三章SPSS数据预处理精要[EB/OL].http://max.bookl18.com/html/2016/0308/37131332.shtm,2016/2016.
  • 5张伟,徐远.两步聚类方法[C]//全国企业信息化与工业工程学术年会,2006.
  • 6Bacher, Johann, Knut Wenzig, and Melanie Vogler."SPSS TwoStep Cluster-a first evaluation."(2004).

二级参考文献14

  • 1Gediminas A,Alexander T. Toward the next generation of recom-mender systems:a survey of the state-of-the-art and possible ex- tensions[ J]. IEEE Trans on Knowledge and Data Engineering ( TKDE ) ,2005,17 ( 6 ) :734 - 749.
  • 2Badrul S,George K,Joseph K,et al. Item-based collaborative fil- tering recommendation algorithms [ C ]//Proc of 10th Internation- al World Wide Web Conference (WWW'01). New York: ACM Press ,2001:285 - 295.
  • 3O'Mahony M P,Hurley N J,Si|vestre G C M. Detecting noise in recommender system databases[ C]//Proc of the 10th Interna- tional Conference on Intelligent User Interfaces ( IUI '06 ). New York : ACM Press ,2006 : 109 - 115.
  • 4Cao Huanhuan, Chen Enhong, Yang Jie, et al. Enhancing recom- mender systems under volatile user interest drifts [ C ]//Proc of the 18th ACM Conference on Information and Knowledse Man- agement ( C1KM'09 ). New York : ACM Press, 2009 : 1257 - 1266.
  • 5Xavier A, Neal L, Pujol J M, et al. The wisdom of the few : a col- laborative filtering approach based on expert opinions from the web[ C-//Proc of the 32nd International ACM SIGIR Confer- ence on Research and Development in Information Retrieval ( SIGIR'09 ). New York : ACM Press ,2009 : 552 - 539.
  • 6Herlocker J L, Konstan J A, Terveen L G, et al. Evaluating col- laborative filtering recommender systems [ J ]. Transactions on In- formation Systems (TOIS) , 2004,22 ( 1 ) : 5 - 53.
  • 7Wang Jun, de Vries A P, Reinders M J T. Unifying user-based and item-based collaborative filtering approaches by similarity fu- sion [ C ]//Proc of the 29th International ACM SIGIR Conference on Research and Development in Information Retrieval ( SIGIR'06 ). New York : ACM Press, 2006 : 501 - 508.
  • 8Cheng Yunghsiang. Exploring passenger anxiety associated with train travel [ J ]. Transportation, 2010,37 ( 6 ) : 875 - 896.
  • 9David Andrich. A rating formulation for ordered response cate- gories [ J ]. Psychometrikia, 1978,43 (4) :561 - 573.
  • 10HuBiyun, Li Zhoujun, Wang Jun. User's latent interest-based collaborative filtering[ C ]//Proc 32nd European Conference on Information Retrieval (ECIR'10). Berlin: Springer-Verlag, 2010:619 - 622.

共引文献2

同被引文献14

引证文献2

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部