期刊文献+

大学生网络交往系统“搭瓣”的设计与实现

The Design and Implementation of Daban: The Network Communication System for College Students
下载PDF
导出
摘要 目的:很多大学生的学习负担重、业余活动种类与次数少、缺乏同兴趣爱好的圈子。为了丰富大学生的生活,增加大学生交友圈子和活动范围,我们建立了大学生网络交流平台“搭瓣”,让大学生找到志趣相同的人与他们一起学习、旅游、活动,丰富其大学生活。方法:基于用户兴趣和社交信任的聚类推荐,基于位置设计网络的地点推荐和基于双边兴趣的社交网络好友推荐。结果:成功登陆搭瓣系统之后,系统根据大学生所填的真实信息用匹配算法对数据库中已有的大学生进行信息的匹配,将推荐与该大学生志趣相投的人、活动、地点等。结论:大学生网络交往系统“搭瓣”通过好友推荐、地点推荐、兴趣推荐等方式匹配到同一时间去做同一件事的同学,使用简便、便于维护和扩展。 Objective: Many college students have a heavy burden of study, fewer leisure activity type and frequency, and lack of the circle of similar hobbies. In order to enrich the lives of college students, and increase college students’ dating circle range, the network communication platform for college students is established, which is called Daban. It helps students to find common interests with them to learn, travel and activities. Method: The clustering recommendation is adopted based on user interest and social trust. The site recommendation is proposed based on location design network. The friend recommendation is put forward based on the social network of bilateral interest. Results: After loging success, like-minded people, activities items and activities location will be recommended to the college students according to their input information and the database. Conclusion: The Daban will find some students to do same thing in same time through recommending friends, activities items and activities location. It is easy to use, easy to maintain and extend.
作者 张文学 郑兴国 连世新 锁小平 Wenxue Zhang;Xingguo Zheng;Shixin Lian;Xiaoping Suo(School of Sciences, Ningxia Medical University, Yinchuan Ningxia;School of Clinical Medicine, Ningxia Medical University, Yinchuan Ningxia)
出处 《计算机科学与应用》 2017年第7期678-687,共10页 Computer Science and Application
基金 宁夏回族自治区大学生创新训练项目:大学生网络交往系统“搭瓣”的设计与实现(NXCX2016116)。
关键词 网络交往 推荐系统 大学生交友 好友推荐 Network Communication Recommendation System College Students Make Friends FriendRecommendation
  • 相关文献

参考文献5

二级参考文献69

  • 1雷雳,陈猛.互联网使用与青少年自我认同的生态关系[J].心理科学进展,2005,13(2):169-177. 被引量:38
  • 2林文龙,刘业政,姜元春.Web浏览预测的Markov模型综述[J].计算机科学,2008,35(1):9-14. 被引量:7
  • 3Bronfenbrenner U.The Ecology of Human Development:Experiments by Nature and Design[M].USA:Harvard University Press,1979:18-22.
  • 4Maczewski M.Exploring Identity Through the Internet:Youth Experiences Online[J].Child&Youth Care Forum,2002,31(2):111-127.
  • 5Lindsay H,Shaw B A,Gant L M.In Defense of the Internet:The Relationship between Internet Communication and Depression,Loneliness,Self-Esteem,and Perceived Social Support[J].Cyber Psychology&Behavior,2002,5(2):157-71.
  • 6Pazzani M J. A framework for collaborative, con-tent-based and demographic filtering [J], Artif In- tell Rev, 1999, 13 (5-6) z 393.
  • 7Lee T Q, Park Y, Park Y. A time-based approach to effective recommender systems using implicit feedback [- J 7. Expert Syst Appl, 2008, 34 (4) . 3055.
  • 8Pan W K, Chen L. GBPR: group preference based Bayesian personalized ranking for one-class collabo- rative filtering [C] //Proceedings of the 23rd Inter- national Conference on Artificial Intelligence. Bei- jing, China: ACM, 2013.
  • 9孔庆超,毛文吉.互联网用户行为的建模与预测[EB/OL]. (2012-09). [2015-11-01]. http.//www. caa. org. cn/ccaa, php? to = ccaa/indextext, action? Aid=29.
  • 10Manavoglu E, Pavlov D, Giles C L. Probabilistic user behavior models [C] //Proeeedings of the 3rd IEEE International Conference on Data Mining. Melbourne, Florida: IEEE, 2003.

共引文献30

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