When I was working on the third homework of data mining course: clustering the short texts, I found this paper in Reference section which turned out be to the one recommended by Mr. Zhang in class. So I tried to implement the GSDMM algorithm proposed myself, of course, with the help of online resources.
This implementation is still on going.
vacabulary.json, with one word and its corresponding id each line.train_tokens.json, with one doc-id and its token list each line.train_topics.json, using for validation.
- Paper
- Yin, J. and Wang, J., 2014, August. A dirichlet multinomial mixture model-based approach for short text clustering. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 233-242).ACM.
- Nguyen, D. Q., Billingsley, R., Du, L., & Johnson, M. (2015). Improving topic models with latent feature word representations. , 3, 299-313.
- Code
- datquocnguyen/jLDADMM: java version
- atefm/pDMM: python version