SCIE, EI, Scopus, INSPEC, DBLP, CSCD, etc.
Citation: | Jun Hu, Bing Wang, Yu Liu, De-Yi Li. Personalized Tag Recommendation Using Social Influence[J]. Journal of Computer Science and Technology, 2012, 27(3): 527-540. DOI: 10.1007/s11390-012-1241-0 |
[1] |
Sigurbjörnsson B, van Zwol R. Flickr tag recommendationbased on collective knowledge. In Proc. the 17th Inter-national Conference on World Wide Web, Beijing, China,Apr. 21-25, 2008, pp.327-336.
|
[2] |
Smeulders A, Worring M, Santini S, Gupta A, Jain R.Content-based image retrieval at the end of the early years.IEEE Transactions Pattern Analysis Machine Intelligence,2000, 22(12): 1349-1380.
|
[3] |
Ames M, Naaman M. Why we tag: Motivations for annota-tion in mobile and online media. In Proc. the 2007 SIGCHIConference on Human Factors in Computing Systems, SanJose, USA, Apr. 28-May 3, 2007, pp.971-980.
|
[4] |
Gemmell J, Ramezani M, Schimoler T, Christiansen L,Mobasher B. The impact of ambiguity and redundancy ontag recommendation in folksonomies. In Proc. the 3rd ACMConference on Recommender Systems, New York City, USA,Oct. 23-25, 2009, pp.45-52.
|
[5] |
Vojnovic M, Cruise J, Gunawardena D, Marbach P. Rankingand suggesting popular items. IEEE Transactions on Know-ledge and Data Engineering, 2009, 21(8): 1133-1146.
|
[6] |
Guan Z Y, Bu J J, Mei Q Z, Chen C, Wang C. Personalizedtag recommendation using graph-based ranking on multi-typeinterrelated objects. In Proc. the 32nd Annual InternationalACM SIGIR Conference on Research and Development in In-formation Retrieval, Boston, USA, July 19-23, 2009, pp.540-547.
|
[7] |
Yin D W, Xue Z Z, Hong L J, Davison B D. A probabilisticmodel for personalized tag prediction. In Proc. the 16th ACM SIGKDD International Conference on Knowledge Discoveryand Data Ming, Washington, USA, Jul. 25-28, 2010, pp.959-968.
|
[8] |
Lipczak M, Milios E. Learning in efficient tag recommenda-tion. In Proc. the 4th ACM Conference on RecommenderSystems, Barcelona, Spain, Sept. 26-30, 2010, pp.167-174.
|
[9] |
Koren Y. Factorization meets the neighborhood: A multi-faceted collaborative filtering model. In Proc. the 14th ACMSIGKDD International Conference on Knowledge Discoveryand Data Mining, Las Vegas, USA, Aug. 24-27, 2008, pp.426-434.
|
[10] |
J?aschke R, Marinho L, Hotho A, Schmidt-Thieme L, StummeG. Tag recommendations in folksonomies. In Proc. the 11thEuropean Conference on Principles and Practice of Know-ledge Discovery in Databases, Warsaw, Poland, September17-21, 2007, pp.506-514.
|
[11] |
Symeonidis P, Nanopoulos A, Manolopoulos Y. Tag recom-mendations based on tensor dimensionality reduction. InProc. the 2nd ACM Conference on Recommender Systems,Lausanne, Switzerland, October 23-25, 2008, pp.43-50.
|
[12] |
Rendle S, Marinho B L, Nanopoulos A, Schmidt-Thieme L.Learning optimal ranking with tensor factorization for tagrecommendation. In Proc. the 15th ACM SIGKDD Interna-tional Conference on Knowledge Discovery and Data Mining,Paris, France, Jun. 28-Jul. 1, 2009, pp.727-736.
|
[13] |
Tatu M, Srikanth M, D'Silva T. Tag recommendations us-ing bookmark content. In Proc. the 2008 ECML/PKDDDiscovery Challenge Workshop, Antwerp, Belgium, Sep. 15-19, 2008, pp.96-107.
|
[14] |
Koren Y. Collaborative filtering with temporal dynamics. InProc. the 15th ACM SIGKDD International Conferenceon Knowledge Discovery and Data Mining, Paris, France,Jun. 28-Jul. 1, 2009, pp.447-456.
|
[15] |
Garg N, Weber I. Personalized, interactive tag recommen-dation for flickr. In Proc. the 2nd ACM Conference onRecommender Systems, Lausanne, Switzerland, October 23-25, 2008, pp.67-74.
|
[16] |
Rae A, Sigurbjornsson B, van Zwol R. Improving tag reco-mmendation using social networks. In Proc. the 9th Inter-national Conference on Adaptivity, Personalization and Fu-sion of Heterogeneous Information, Paris, France, Apr. 28-30,2010, pp.92-99.
|
[17] |
Ma H, King I, Lyu M R. Learning to recommend with explicitand implicit social relations. ACM Transactions on Intelli-gent Systems and Technology, 2011, 2(3): Article No. 29.
|
[18] |
Lipczak M, Milios E. The impact of resource title on tagsin collaborative tagging systems. In Proc. the 21st ACMConference on Hypertext and Hypermedia, Toronto, Canada,Jun. 13-16, 2010, pp.179-188.
|
[19] |
Mislove A, Koppula H S, Gummadi K P, Drusche P, Bhat-tacharjee B. Growth of the flickr social network. In Proc.the 1st Workshop on Online Social Networks, Seattle, USA,Aug. 18, 2008, pp.25-30.
|
[20] |
Cha M Y, Mislove A, Gummadi K P. A measurement-drivenanalysis of information propagation in the flickr social net-work. In Proc. the 18th International Conference on WorldWide Web, Madrid, Spain, Apr. 20-24, 2009, pp.721-730.
|
[21] |
Li D Y, Du Y. Artifical Intelligence With Uncertainty. BocaRaton, Florida: Chapman and Hall/CRC Press, 2008.
|
[22] |
Wu L, Yang L J, Yu N H, Hua X S. Learning to tag. InProc. the 18th International Conference on World WideWeb, Madrid, Spain, Apr. 20-24, 2009, pp.361-370.
|
[23] |
Liu N N, Yang Q. Eigenrank: A ranking-oriented approachto collaborative filtering. In Proc. the 31st Annual ACMSIGIR International Conference on Research and Develop-ment in Information Retrieval, Singapore, Singapore, Jul. 20-24, 2008, pp.83-90.
|
[24] |
Shen D, Sun J T, Yang Q, Chen Z. A comparison of implicitand explicit links for web page classification. In Proc. the15th International Conference on World Wide Web, Edin-burgh, Scotland, May 23-26, 2006, pp.643-650.
|
[1] | Yu-Liang Ma, Ye Yuan, Fei-Da Zhu, Guo-Ren Wang, Jing Xiao, Jian-Zong Wang. Who Should Be Invited to My Party: A Size-Constrained k-Core Problem in Social Networks[J]. Journal of Computer Science and Technology, 2019, 34(1): 170-184. DOI: 10.1007/s11390-019-1905-0 |
[2] | Mehdi Azaouzi, Lotfi Ben Romdhane. An Efficient Two-Phase Model for Computing Influential Nodes in Social Networks Using Social Actions[J]. Journal of Computer Science and Technology, 2018, 33(2): 286-304. DOI: 10.1007/s11390-018-1820-9 |
[3] | Bo-Lei Zhang, Zhu-Zhong Qian, Wen-Zhong Li, Bin Tang, Sang-Lu Lu, Xiaoming Fu. Budget Allocation for Maximizing Viral Advertising in Social Networks[J]. Journal of Computer Science and Technology, 2016, 31(4): 759-775. DOI: 10.1007/s11390-016-1661-3 |
[4] | Mingxuan Yuan, Lei Chen, Philip S. YU, Hong Mei. Protect You More Than Blank: Anti-learning Sensitive User Information in the Social Networks[J]. Journal of Computer Science and Technology, 2014, 29(5): 762-776. DOI: 10.1007/s11390-014-1466-1 |
[5] | Rafael Messias Martins, Gabriel Faria Andery, Henry Heberle, Fernando Vieira Paulovich, Alneu de Andrade Lopes, Helio Pedrini, Rosane Minghim. Multidimensional Projections for Visual Analysis of Social Networks[J]. Journal of Computer Science and Technology, 2012, 27(4): 791-810. DOI: 10.1007/s11390-012-1265-5 |
[6] | Philip Leroux, Student, Bart Dhoedt, Piet Demeester, Filip De Turck. Performance Characterization of Game Recommendation Algorithms on Online Social Network Sites[J]. Journal of Computer Science and Technology, 2012, 27(3): 611-623. DOI: 10.1007/s11390-012-1248-6 |
[7] | Farnoush Farhadi, Maryam Sorkhi, Sattar Hashemi, Ali Hamzeh. An Effective Framework for Fast Expert Mining in Collaboration Networks: A Group-Oriented and Cost-Based Method[J]. Journal of Computer Science and Technology, 2012, 27(3): 577-590. DOI: 10.1007/s11390-012-1245-9 |
[8] | Jian-Yun Liu, Yu-Hang Zhao, Zhao-Xiang Zhang, Yun-Hong Wang, Xue-Mei Yuan, Lei Hu, Zhen-Jiang Dong. Spam Short Messages Detection via Mining Social Networks[J]. Journal of Computer Science and Technology, 2012, 27(3): 506-514. DOI: 10.1007/s11390-012-1239-7 |
[9] | Zhi-Hao Wu, You-Fang Lin, Steve Gregory, Huai-Yu Wan, Student, Sheng-Feng Tian. Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks[J]. Journal of Computer Science and Technology, 2012, 27(3): 468-479. DOI: 10.1007/s11390-012-1236-x |
[10] | Mao-Guo Gong, Ling-Jun Zhang, Jing-Jing Ma, Li-Cheng Jiao. Community Detection in Dynamic Social Networks Based on Multiobjective Immune Algorithm[J]. Journal of Computer Science and Technology, 2012, 27(3): 455-467. DOI: 10.1007/s11390-012-1235-y |