基于社会标签和时间兴趣演变模型的微博推荐算法

Yuan Zhen-ming; Huang Chi; Sun Xiao-yan; Li Xing-xing; Xu Dong-rong

doi:10.1631/FITEE.1400368

Your Location：

Home >

Browse articles >

基于社会标签和时间兴趣演变模型的微博推荐算法

服务可用性专题 | Updated：2022-06-06

- 基于社会标签和时间兴趣演变模型的微博推荐算法
- A microblog recommendation algorithm based on social tagging and a temporal interest evolution model*
- 信息与电子工程前沿（英文） 2015年16卷第7期页码：532-540
- Affiliations：
  
  1.School of Information Science and Engineering, Hangzhou Normal University, Hangzhou 311121, China
  2.MRI Unit & Epidemiology Division, Psychiatry Department, Columbia University & New York State Psychiatric Institute, New York 10032, USA
- Author bio：
  
  ‡Corresponding Author
- Funds：
  
  *Project supported by the Natural Science Foundation of Zhejiang Province, China (No. LZ12F02004), the Program of Xinmiao Talent of Zhejiang Province, China (No. ZX13005002064), and the National Natural Science Foundation of China (No. 81471734)
- DOI：10.1631/FITEE.1400368
  中图分类号：
- 收稿：2014-10-30，
  
  修回：2015-06-08，
  
  录用：2015-04-08，
  
  纸质出版：2015-07
- Accepted：
Scan QR Code
基于社会标签和时间兴趣演变模型的微博推荐算法[J]. 信息与电子工程前沿（英文）, 2015,16(7):532-540.

Yuan Zhen-ming, Huang Chi, Sun Xiao-yan, et al. A microblog recommendation algorithm based on social tagging and a temporal interest evolution model*[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(7): 532-540.
基于社会标签和时间兴趣演变模型的微博推荐算法[J]. 信息与电子工程前沿（英文）, 2015,16(7):532-540. DOI： 10.1631/FITEE.1400368.

Yuan Zhen-ming, Huang Chi, Sun Xiao-yan, et al. A microblog recommendation algorithm based on social tagging and a temporal interest evolution model*[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(7): 532-540. DOI： 10.1631/FITEE.1400368.

摘要

目的

微博推荐面临用户冷启动和主题兴趣变化的挑战。研究考虑主题兴趣变化的个性化微博推荐算法，可在一定程度上同时解决用户冷启动问题。

创新点

提出一种基于时间兴趣演变模型和社会标签预测的协同过滤推荐算法。该算法充分利用社会网络和标签热度随时间的演变模型，提高了推荐准确率。

方法

首先，用三个矩阵建模用户、标签和微博之间的关系（图2）。然后根据标签的兴趣演变模型优化每个微博的标签评分（图3）。对于用户冷启动问题，设计一种基于社区发现和最大标签投票算法来预测用户相关的标签。最后，给用户推荐具有最大候选标签集概率的前n个微博（图1）。

结论

在新浪微博数据集上的实验验证了所提算法在获得好的招回率和准确率的同时，可以较好地符合时间演变性能。问卷调查也证明了在冷启动发生时推荐结果的用户满意度。

Abstract

Personalized microblog recommendations face challenges of user cold-start problems and the interest evolution of topics. In this paper

we propose a collaborative filtering recommendation algorithm based on a temporal interest evolution model and social tag prediction. Three matrices are first prepared to model the relationship between users

关键词

Keywords

references

MG Armentano , D Godoy , AA Amandi . Followee recommendation based on text analysis of micro-blogging activity . Inform Syst , 2013 . 38 ( 8 ): 1116 - 1127 . DOI: 10.1016/j.is.2013.05.009 http://doi.org/10.1016/j.is.2013.05.009 .

M Balabanović , Y Shoham . Fab: content-based, collaborative recommendation . Commun ACM , 1997 . 40 ( 3 ): 66 - 72 . DOI: 10.1145/245108.245124 http://doi.org/10.1145/245108.245124 .

JS Breese , D Heckerman , C Kadie . Empirical analysis of predictive algorithms for collaborative filtering . 1998 . Proc. 14th Conf. on Uncertainty in Artificial Intelligence . 43 - 52 . .

M Cataldi , L di Caro , C Schifanella . Emerging topic detection on Twitter based on temporal and social terms evaluation . 2010 . Proc. 10th Int. Workshop on Multimedia Data Mining, Article 4 . DOI: 10.1145/1814245.1814249 http://doi.org/10.1145/1814245.1814249 .

K Chen , T Chen , G Zheng , 等 . Collaborative personalized tweet recommendation . 2012 . Proc. 35th Int. ACM SIGIR Conf. on Research and Development in Information Retrieval . 661 - 670 . DOI: 10.1145/2348283.2348372 http://doi.org/10.1145/2348283.2348372 .

C Chi , Q Liao , Y Pan , 等 . Smarter social collaboration at IBM research . 2011 . Proc. ACM Conf. on Computer Supported Cooperative Work . 159 - 166 . DOI: 10.1145/1958824.1958848 http://doi.org/10.1145/1958824.1958848 .

AL Deng , YY Zhu , B Shi . A collaborative filtering recommendation algorithm based on item rating prediction . J Softw , 2003 . 14 ( 9 ): 1621 - 1628 . (in Chinese) .

C Ding , T Li , W Peng . Nonnegative matrix factorization and probabilistic latent semantic indexing: equivalence chi-square statistic, and a hybrid method . 2006 . Proc. AAAI Conf. on Artificial Intelligence . 342 - 347 . .

Y Ding , X Li . Time weight collaborative filtering . 2005 . Proc. 14th ACM Int. Conf. on Information and Knowledge Management . 485 - 492 . DOI: 10.1145/1099554.1099689 http://doi.org/10.1145/1099554.1099689 .

D Goldberg , D Nichols , BM Oki , 等 . Using collaborative filtering to weave an information tapestry . Commun ACM , 1992 . 35 ( 12 ): 61 - 70 . DOI: 10.1145/138859.138867 http://doi.org/10.1145/138859.138867 .

I Guy , N Zwerdling , I Ronen , 等 . Social media recommendation based on people and tags . 2010 . Proc. 33rd Int. ACM SIGIR Conf. on Research and Development in Information Retrieval . 194 - 201 . DOI: 10.1145/1835449.1835484 http://doi.org/10.1145/1835449.1835484 .

M Jain , S Rajyalakshmi , RM Tripathy , 等 . Temporal analysis of user behavior and topic evolution on Twitter . 2013 . Proc. 2nd Int. Conf. on Big Data Analytics . 22 - 36 . DOI: 10.1007/978-3-319-03689-2_2 http://doi.org/10.1007/978-3-319-03689-2_2 .

G Karypis . Evaluation of item-based top- N recommendation algorithms . 2001 . Proc. 10th Int. Conf. on Information and Knowledge Management . 247 - 254 . DOI: 10.1145/502585.502627 http://doi.org/10.1145/502585.502627 .

BM Kim , Q Li , CS Park , 等 . A new approach for combining content-based and collaborative filters . J Intell Inform Syst , 2006 . 27 ( 1 ): 79 - 91 . DOI: 10.1007/s10844-006-8771-2 http://doi.org/10.1007/s10844-006-8771-2 .

Y Koren . Factorization meets the neighborhood: a multifaceted collaborative filtering model . 2008 . Proc. 14th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining . 426 - 434 . DOI: 10.1145/1401890.1401944 http://doi.org/10.1145/1401890.1401944 .

Y Koren . Collaborative filtering with temporal dynamics . Commun ACM , 2010 . 53 ( 4 ): 89 - 97 . DOI: 10.1145/1721654.1721677 http://doi.org/10.1145/1721654.1721677 .

XW Meng , X Hu , LC Wang , 等 . Mobile recommender systems and their applications . J Softw , 2013 . 24 ( 1 ): 91 - 108 . (in Chinese) .

ME Newman . Fast algorithm for detecting community structure in networks . Phys Rev E , 2004 . 69 066133 DOI: 10.1103/PhysRevE.69.066133 http://doi.org/10.1103/PhysRevE.69.066133 .

MJ Pazzani , D Billsus . Content-based recommendation systems . Adapt Web , 2007 . 4321 325 - 341 . DOI: 10.1007/978-3-540-72079-9_10 http://doi.org/10.1007/978-3-540-72079-9_10 .

B Sarwar , G Karypis , J Konstan , 等 . Item-based collaborative filtering recommendation algorithms . 2001 . Proc. 10th Int. Conf. on World Wide Web . 285 - 295 . DOI: 10.1145/371920.372071 http://doi.org/10.1145/371920.372071 .

L Weigang , EFO Sandes , J Zheng , 等 . Querying dynamic communities in online social networks . J Zhejiang Univ-Sci C (Comput & Electron) , 2014 . 15 ( 2 ): 81 - 90 . DOI: 10.1631/jzus.C1300281 http://doi.org/10.1631/jzus.C1300281 .

H Wen , L Fang , L Guan . A hybrid approach for personalized recommendation of news on the Web . Expert Syst Appl , 2012 . 39 ( 5 ): 5806 - 5814 . DOI: 10.1016/j.eswa.2011.11.087 http://doi.org/10.1016/j.eswa.2011.11.087 .

D Wu , Z Yuan , K Yu , 等 . Temporal social tagging based collaborative filtering recommender for digital library . 2012 . Proc. 14th Int. Conf. on Asia-Pacific Digital Libraries . 199 - 208 . DOI: 10.1007/978-3-642-34752-8_26 http://doi.org/10.1007/978-3-642-34752-8_26 .

CX Xing , FR Gao , SN Zhan , 等 . A collaborative filtering recommendation algorithm incorporated with user interest change . J Comput Res Devel , 2007 . 44 ( 2 ): 296 - 301 . (in Chinese) .

MC Yang , HC Rim . Identifying interesting Twitter contents using topical analysis . Expert Syst Appl , 2014 . 41 ( 9 ): 4330 - 4336 . DOI: 10.1016/j.eswa.2013.12.051 http://doi.org/10.1016/j.eswa.2013.12.051 .

C Yu , J Xu , X Du . Recommendation algorithm combining the user-based classified regression and the item-based filtering . 2006 . Proc. 8th Int. Conf. on Electronic Commerce . 574 - 578 . DOI: 10.1145/1151454.1151463 http://doi.org/10.1145/1151454.1151463 .

Z Yuan , T Yu , J Zhang . A social tagging based collaborative filtering recommendation algorithm for digital library . 2011 . Proc. 13th Int. Conf. on Asia-Pacific Digital Libraries . 192 - 201 . DOI: 10.1007/978-3-642-24826-9_25 http://doi.org/10.1007/978-3-642-24826-9_25 .

K Zhou , SH Yang , H Zha . Functional matrix factorizations for cold-start recommendation . 2011 . Proc. 34th Int. ACM SIGIR Conf. on Research and Development in Information Retrieval . 315 - 324 . DOI: 10.1145/2009916.2009961 http://doi.org/10.1145/2009916.2009961 .

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

A novel confidence estimation method for heterogeneous implicit feedback

A new item-based deep network structure using a restricted Boltzmann machine for collaborative filtering

Preference transfer model in collaborative filtering for implicit data

Scientific articles recommendation with topic regression and relational matrix factorization