The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Topic-link LDA: joint models of topic and author community
Abstract
Given a large-scale linked document collection, such as a collection of blog posts or a research literature archive, there are two fundamental problems that have generated a lot of interest in the research community. One is to identify a set of high-level topics covered by the documents in the collection; the other is to uncover and analyze the social network of the authors of the documents. So far these problems have been viewed as separate problems and considered independently from each other. In this paper we argue that these two problems are in fact inter-dependent and should be addressed together. We develop a Bayesian hierarchical approach that performs topic modeling and author community discovery in one unified framework. The effectiveness of our model is demonstrated on two blog data sets in different domains and one research paper citation data from CiteSeer.
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Cites
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Griffiths, T. L., & Steyvers, M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307752101 · Cited by 6,049
An Introduction to Variational Methods for Graphical Models
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., & Saul, L. K. (1999) · Machine Learning · doi:10.1023/a:1007665907178 · Cited by 3,791
Blei, D. M., & Lafferty, J. D. (2006) · Proceedings of the 23rd international conference on Machine learning - ICML '06 · doi:10.1145/1143844.1143859 · Cited by 2,386
The author-topic model for authors and documents
Rosen‐Zvi, M., Griffiths, T. L., Steyvers, M., & Smyth, P. (2004) · Uncertainty in Artificial Intelligence · doi:10.5555/1036843.1036902 · Cited by 1,280
Automating the Construction of Internet Portals with Machine Learning
McCallum, A. K., Nigam, K., Rennie, J., & Seymore, K. (2000) · Information Retrieval · doi:10.1023/a:1009953814988 · Cited by 1,280
Inferring Web communities from link topology
Gibson, D., Kleinberg, J., & Raghavan, P. (1998) · Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems links, objects, time and space---structure in hypermedia systems - HYPERTEXT '98 · doi:10.1145/276627.276652 · Cited by 768
Graph mining: Laws, generators, and algorithms
Chakrabarti, D., & Faloutsos, C. (2006) · ACM Computing Surveys · doi:10.1145/1132952.1132954 · Cited by 609
Relational Topic Models for Document Networks
Chang, J., & Blei, D. M. (2009) · Cited by 507
Mixed-membership models of scientific publications
Erosheva, E., Fienberg, S., & Lafferty, J. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307760101 · Cited by 442
Cited by
Empirical study of topic modeling in Twitter
Hong, L., & Davison, B. D. (2010) · Proceedings of the First Workshop on Social Media Analytics · doi:10.1145/1964858.1964870 · Cited by 1,120
Inferring Networks of Substitutable and Complementary Products
McAuley, J., Pandey, R., & Leskovec, J. (2015) · Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/2783258.2783381 · Cited by 645
Discovering social circles in ego networks
Mcauley, J., & Leskovec, J. (2014) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/2556612 · Cited by 366
A survey of community search over big graphs
Fang, Y., Huang, X., Qin, L., Zhang, Y., Zhang, W., Cheng, R., & Lin, X. (2020) · The VLDB Journal · doi:10.1007/s00778-019-00556-x · Cited by 339
Effective community search for large attributed graphs
Fang, Y., Cheng, R., Luo, S., & Hu, J. (2016) · Proceedings of the VLDB Endowment · doi:10.14778/2994509.2994538 · Cited by 317
Metadata
- Authors
- Liu, Y., Niculescu-Mizil, A., & Gryc, W.
- Venue
- Proceedings of the 26th Annual International Conference on Machine Learning
- Publisher
- ACM
- Published
- 2009-06-14
- Pages
- 665-672
- OpenAlex
- W2130978632
- Cited by
- 288
- References
- 17
- FWCI
- 11.28
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Liu, Y., Niculescu-Mizil, A., & Gryc, W. (2009). Topic-link LDA: joint models of topic and author community. Proceedings of the 26th Annual International Conference on Machine Learning. https://doi.org/10.1145/1553374.1553460
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
