Modeling topic dependencies in semantically coherent text spans with copulas - Archive ouverte HAL Access content directly
Conference Papers Year : 2016

Modeling topic dependencies in semantically coherent text spans with copulas

Abstract

The exchangeability assumption in topic models like Latent Dirichlet Allocation (LDA) often results in inferring inconsistent topics for the words of text spans like noun-phrases, which are usually expected to be topically coherent. We propose copulaLDA, that extends LDA by integrating part of the text structure to the model and relaxes the conditional independence assumption between the word-specific latent topics given the per-document topic distributions. To this end, we assume that the words of text spans like noun-phrases are topically bound and we model this dependence with copulas. We demonstrate empirically the effectiveness of copulaLDA on both intrinsic and extrinsic evaluation tasks on several publicly available corpora.

Keywords

No file

Dates and versions

hal-01406613 , version 1 (01-12-2016)

Identifiers

  • HAL Id : hal-01406613 , version 1

Cite

Georgios Balikas, Hesam Amoualian, Marianne Clausel, Gaussier Eric, Massih-Reza Amini. Modeling topic dependencies in semantically coherent text spans with copulas. International Conference on Computational Linguistics (COLING), Dec 2016, Osaka, Japan. ⟨hal-01406613⟩
268 View
0 Download

Share

Gmail Mastodon Facebook X LinkedIn More