Tree-structured hierarchical Dirichlet process

Md Hijbul Alam; Jaakko Peltonen; Jyrki Nummenmaa; Kalervo Järvelin

doi:10.1007/978-3-319-99608-0_33

Tree-structured hierarchical Dirichlet process

Md Hijbul Alam, Jaakko Peltonen^*, Jyrki Nummenmaa, Kalervo Järvelin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

In many domains, document sets are hierarchically organized such as message forums having multiple levels of sections. Analysis of latent topics within such content is crucial for tasks like trend and user interest analysis. Nonparametric topic models are a powerful approach, but traditional Hierarchical Dirichlet Processes (HDPs) are unable to fully take into account topic sharing across deep hierarchical structure. We propose the Tree-structured Hierarchical Dirichlet Process, allowing Dirichlet process based topic modeling over a given tree structure of arbitrary size and height, where documents can arise at all tree nodes. Experiments on a hierarchical social message forum and a product reviews forum demonstrate better generalization performance than traditional HDPs in terms of ability to model new data and classify documents to sections.

Original language	English
Title of host publication	Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference
Editors	Sara Rodríguez, Javier Prieto, Pedro Faria, María N. Moreno, Santiago Mazuelas, Elena M. Navarro, Slawomir Klos, Alberto Fernández, M. Dolores Jiménez-López
Pages	291-299
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-319-99608-0_33
Publication status	Published - 1 Jan 2019
MoE publication type	A4 Article in a conference publication
Event	International Conference on Distributed Computing and Artificial Intelligence - Toledo, Spain Duration: 20 Jun 2018 → 22 Jun 2018 Conference number: 15

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	801
ISSN (Print)	2194-5357

Conference

Conference	International Conference on Distributed Computing and Artificial Intelligence
Abbreviated title	DCAI
Country/Territory	Spain
City	Toledo
Period	20/06/2018 → 22/06/2018

Keywords

Hierarchical Dirichlet Processes
Message forum
Topic modeling

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10.1007/978-3-319-99608-0_33

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Alam, M. H., Peltonen, J., Nummenmaa, J., & Järvelin, K. (2019). Tree-structured hierarchical Dirichlet process. In S. Rodríguez, J. Prieto, P. Faria, M. N. Moreno, S. Mazuelas, E. M. Navarro, S. Klos, A. Fernández, & M. D. Jiménez-López (Eds.), Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference (pp. 291-299). (Advances in Intelligent Systems and Computing; Vol. 801). https://doi.org/10.1007/978-3-319-99608-0_33

Alam, Md Hijbul ; Peltonen, Jaakko ; Nummenmaa, Jyrki ; Järvelin, Kalervo. / Tree-structured hierarchical Dirichlet process. Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. editor / Sara Rodríguez ; Javier Prieto ; Pedro Faria ; María N. Moreno ; Santiago Mazuelas ; Elena M. Navarro ; Slawomir Klos ; Alberto Fernández ; M. Dolores Jiménez-López. 2019. pp. 291-299 (Advances in Intelligent Systems and Computing).

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abstract = "In many domains, document sets are hierarchically organized such as message forums having multiple levels of sections. Analysis of latent topics within such content is crucial for tasks like trend and user interest analysis. Nonparametric topic models are a powerful approach, but traditional Hierarchical Dirichlet Processes (HDPs) are unable to fully take into account topic sharing across deep hierarchical structure. We propose the Tree-structured Hierarchical Dirichlet Process, allowing Dirichlet process based topic modeling over a given tree structure of arbitrary size and height, where documents can arise at all tree nodes. Experiments on a hierarchical social message forum and a product reviews forum demonstrate better generalization performance than traditional HDPs in terms of ability to model new data and classify documents to sections.",

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Alam, MH, Peltonen, J, Nummenmaa, J & Järvelin, K 2019, Tree-structured hierarchical Dirichlet process. in S Rodríguez, J Prieto, P Faria, MN Moreno, S Mazuelas, EM Navarro, S Klos, A Fernández & MD Jiménez-López (eds), Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. Advances in Intelligent Systems and Computing, vol. 801, pp. 291-299, International Conference on Distributed Computing and Artificial Intelligence, Toledo, Spain, 20/06/2018. https://doi.org/10.1007/978-3-319-99608-0_33

Tree-structured hierarchical Dirichlet process. / Alam, Md Hijbul; Peltonen, Jaakko; Nummenmaa, Jyrki; Järvelin, Kalervo.

Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. ed. / Sara Rodríguez; Javier Prieto; Pedro Faria; María N. Moreno; Santiago Mazuelas; Elena M. Navarro; Slawomir Klos; Alberto Fernández; M. Dolores Jiménez-López. 2019. p. 291-299 (Advances in Intelligent Systems and Computing; Vol. 801).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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T1 - Tree-structured hierarchical Dirichlet process

AU - Alam, Md Hijbul

AU - Peltonen, Jaakko

AU - Nummenmaa, Jyrki

AU - Järvelin, Kalervo

N1 - Conference code: 15

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AB - In many domains, document sets are hierarchically organized such as message forums having multiple levels of sections. Analysis of latent topics within such content is crucial for tasks like trend and user interest analysis. Nonparametric topic models are a powerful approach, but traditional Hierarchical Dirichlet Processes (HDPs) are unable to fully take into account topic sharing across deep hierarchical structure. We propose the Tree-structured Hierarchical Dirichlet Process, allowing Dirichlet process based topic modeling over a given tree structure of arbitrary size and height, where documents can arise at all tree nodes. Experiments on a hierarchical social message forum and a product reviews forum demonstrate better generalization performance than traditional HDPs in terms of ability to model new data and classify documents to sections.

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BT - Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference

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Alam MH, Peltonen J, Nummenmaa J, Järvelin K. Tree-structured hierarchical Dirichlet process. In Rodríguez S, Prieto J, Faria P, Moreno MN, Mazuelas S, Navarro EM, Klos S, Fernández A, Jiménez-López MD, editors, Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. 2019. p. 291-299. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-99608-0_33

Tree-structured hierarchical Dirichlet process

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