DOAJ Open Access 2017

Topical Text Network Construction Method Based on Gibbs Sampling Results

ZHANG Zhiyuan,YANG Hongjing,ZHAO Yue

Lihat Sumber DOI

Abstrak

Mining the probability distribution of topic words in document collection can make a summary understanding of the document content.Further exploring the connection relationship between words in a given topic not only riches the meaning of topic words,but also reveals the hierarchy and aggregation of topics.For the labeled document collection,this paper proposes a method to compute the conditional probability of two words under a given topic based on Gibbs sampling outputs of labeled Latent Dirichlet Allocation(LDA),and a topical text network is also constructed.Compared with Pointwise Labeled-LDA(PL-LDA) model,this method does not extend the original document and needs less computation cost and shorter time.Experiments on the data set of aviation safety reports show that,for topics with many labeled words,this method can better display the distribution of subject words and the complex relationship between them.

Topik & Kata Kunci

Computer engineering. Computer hardware Computer software

Penulis (1)

ZHANG Zhiyuan,YANG Hongjing,ZHAO Yue

Format Sitasi

APA MLA BibTeX

Yue, Z.Z.H. (2017). Topical Text Network Construction Method Based on Gibbs Sampling Results. https://doi.org/10.3969/j.issn.1000-3428.2017.06.025

Akses Cepat

Lihat di Sumber doi.org/10.3969/j.issn.1000-3428.2017.06.025

Informasi Jurnal

Tahun Terbit: 2017
Sumber Database: DOAJ
DOI: 10.3969/j.issn.1000-3428.2017.06.025
Akses: Open Access ✓