Exploiting temporal authors interests via temporal-author-topic modeling

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5678 LNAI, Issue , 2009, Pages 435-443

  Daud, Ali ^a   Li, Juanzi ^a   Zhou, Lizhu ^a   Muhammad, Faqir ^b  

^a TSINGHUA UNIVERSITY   (China)

^b ALLAMA IQBAL OPEN UNIVERSITY   (Pakistan)

Author keywords

Temporal authors interests; Topic modeling; Unsupervised learning

Indexed keywords

DATA SETS; GRAPH CONNECTIVITY; INTRINSIC STRUCTURES; MIXTURE DISTRIBUTIONS; MODELING APPROACH; RESEARCH PAPERS; TEMPORAL AUTHORS INTERESTS; TIME FACTORS; TIME PERIODS; TIME STAMPS; TOPIC MODELING;

RESEARCH; UNSUPERVISED LEARNING;

SEMANTICS;

EID: 70350632753     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03348-3_42     Document Type: Conference Paper

References (18)

1. Andrieu, C., Freitas, N.D., Doucet, A., Jordan, M.I.: An Introduction to MCMC for Machine Learning. Journal of Machine Learning 50, 5-43 (2003)
2. Azzopardi, L., Girolami, M., Risjbergen, K.V.: Investigating the Relationship between Language Model Perplexity and IR Precision-Recall Measures. In: Proc. of the 26th ACM SIGIR, Toronto, Canada, July 28-August 1 (2003)
3. Balog, K., Bogers, T., Azzopardi, L., Rijke, M.D., Bosch, A.V.D.: Broad Expertise Retrieval in Sparse Data Environments. In: Proc. of the SIGIR, pp. 551-558 (2007)
4. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet Allocation. Journal of Machine Learning Research 3, 993-1022 (2003)
5. Daud, A., Li, J., Zhou, L., Muhammad, F.: A Generalized Topic Modeling Approach for Maven Search. In: Proc. of the APWeb-WAIM, Suzhou, China, April 2-4 (2009)
6. DBLP Bibliography Database, http://www.informatik.uni-trier.de/~ley/db/
7. Diederich, J., Kindermann, J., Leopold, E., Paass, G.: Authorship Attribution with Support Vector Machines. Applied Intelligence 19(1) (2003)
8. Erten, C., Harding, P.J., Kobourov, S.G., Wampler, K., Yee, G.: Exploring the Computing Literature using Temporal Graph Visualization. Technical Report, Department of Computer Science, University of Arizona (2003)
9. Gray, A., Sallis, P., MacDonell, S.: Softwareforensics: Extending Authorship Analysis Techniques to Computer Programs. In: Proc. of the 3rd IAFL, Durham NC (1997)
10. Griffiths, T.L., Steyvers, M.: Finding Scientific Topics. In: Proc. of the National Academy of Sciences, USA, pp. 5228-5235 (2004)
11. Zhang, J., Tang, J., Li, J.: Expert Finding in a Social Network. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 1066-1069. Springer, Heidelberg (2007)
12. McCallum, A.: Multi-label Text Classification with A Mixture Model Trained by EM. In: Proc. of AAAI 1999 Workshop on Text Learning (1999)
13. Mutschke, P.: Mining Networks and Central Entities in Digital Libraries: A Graph Theoretic Approach applied to Co-author Networks. Intelligent Data Analysis, 155-166 (2003)
14. Rosen-Zvi, M., Griffiths, T., Steyvers, M.: Smyth. P.: The Author-Topic Model for Authors and Documents. In: Proc. of the 20th conference on UAI, Canada (2004)
15. Steyvers, M., Smyth, P., Griffiths, T.: Probabilistic Author-Topic Models for Information Discovery. In: Proc. of the 10th ACM SIGKDD, Seattle, Washington (2004)
16. Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., Su, Z.: ArnetMiner: Extraction and Mining of Academic Social Networks. In: Proc. of the 14th ACM SIGKDD (2008)
17. Wang, X., McCallum, A.: Topics over Time: A Non-Markov Continuous-Time Model of Topical Trends. In: Proc. of the 12th ACM SIGKDD, pp. 424-433 (2006)
18. White, S., Smyth, P.: Algorithms for Estimating Relative Importance in Networks. In: Proc. of the 9th ACM SIGKDD, pp. 266-275 (2003)