Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models
With the growth of social media information on the Web, performing clustering on different types of data is a challenging task. Statistical approaches are widely used to tackle this task. Among the successful statistical approaches, finite mixture models have received a lot attention thanks to their...
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| Format: | Article |
| Language: | English |
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LibraryPress@UF
2021-04-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/128506 |
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| author | xuanbo su Nizar Bouguila Nuha Zamzami |
| author_facet | xuanbo su Nizar Bouguila Nuha Zamzami |
| author_sort | xuanbo su |
| collection | DOAJ |
| description | With the growth of social media information on the Web, performing clustering on different types of data is a challenging task.
Statistical approaches are widely used to tackle this task. Among the successful statistical approaches, finite mixture models have received a lot attention thanks to their flexibility. There are already many finite mixture models to cope with this task, but the Exponential Multinomial Scaled Dirichlet Distributions (EMSD) has recently shown to attain higher accuracy compared to other state-of-the-art generative models for count data clustering. Thus, in this paper, we present a Bayesian learning method based on Markov Chain Monte Carlo and Metropolis-Hastings algorithm for learning this model parameters. This proposed method is validated via extensive simulations and comparison with multinomial based mixture models. |
| format | Article |
| id | doaj-art-7f3f89dfe2ab492eb36c3ad502b2e4db |
| institution | DOAJ |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2021-04-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-7f3f89dfe2ab492eb36c3ad502b2e4db2025-08-20T03:05:50ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622021-04-013410.32473/flairs.v34i1.12850662899Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Modelsxuanbo su0Nizar BouguilaNuha ZamzamiConcordia Institute for Information Systems Engineering (CIISE), Concordia Uinversity, Montreal, QC, CanadaWith the growth of social media information on the Web, performing clustering on different types of data is a challenging task. Statistical approaches are widely used to tackle this task. Among the successful statistical approaches, finite mixture models have received a lot attention thanks to their flexibility. There are already many finite mixture models to cope with this task, but the Exponential Multinomial Scaled Dirichlet Distributions (EMSD) has recently shown to attain higher accuracy compared to other state-of-the-art generative models for count data clustering. Thus, in this paper, we present a Bayesian learning method based on Markov Chain Monte Carlo and Metropolis-Hastings algorithm for learning this model parameters. This proposed method is validated via extensive simulations and comparison with multinomial based mixture models.https://journals.flvc.org/FLAIRS/article/view/128506 |
| spellingShingle | xuanbo su Nizar Bouguila Nuha Zamzami Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| title | Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models |
| title_full | Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models |
| title_fullStr | Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models |
| title_full_unstemmed | Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models |
| title_short | Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models |
| title_sort | covid 19 news clustering using mcmc based learing of finite emsd mixture models |
| url | https://journals.flvc.org/FLAIRS/article/view/128506 |
| work_keys_str_mv | AT xuanbosu covid19newsclusteringusingmcmcbasedlearingoffiniteemsdmixturemodels AT nizarbouguila covid19newsclusteringusingmcmcbasedlearingoffiniteemsdmixturemodels AT nuhazamzami covid19newsclusteringusingmcmcbasedlearingoffiniteemsdmixturemodels |