The nested Indian buffet process for flexible topic modeling

Jen-Tzung Chien*, Ying Lan Chang

*此作品的通信作者

研究成果: Conference article同行評審

2 引文 斯高帕斯(Scopus)

摘要

This paper presents a flexible topic model based on the nested Indian buffet process (nIBP). The flexibility is achieved by relaxing three constraints: (1) number of topics is fixed, (2) topics are independent, and (3) topic hierarchy for a document is limited by a single tree path. Bayesian nonparametric learning is conducted to build a tree model where the number of topics and the topic hierarchies are automatically learnt from the given data. In particular, we propose the nIBP to construct the topic mixture model for representation of heterogeneous documents where the mixture components are flexibly selected from tree nodes or dishes that a document or customer chooses in Indian buffet process. The selection is performed in a nested and hierarchical manner. The experiments on document representation show the benefits of using the proposed nIBP.

原文English
頁(從 - 到)1434-1437
頁數4
期刊Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
出版狀態Published - 1 一月 2014
事件15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014 - Singapore, Singapore
持續時間: 14 九月 201418 九月 2014

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