NDLI: An Automatic Multi-domain Thesauri Construction Method Based on LDA

Content Provider	IEEE Xplore Digital Library
Author	Na Ni Kai Liu Yaodong Li
Copyright Year	2011
Abstract	This paper proposed a method for building domain-specific thesauri automatically from plain text corpus based on Latent Dirichlet Allocation (LDA). This method consists of two steps: 1) discovering domain-specific terms from document collections of multiple domains, and 2) learning hierarchical relations between the associated terms of each domain. The novelty of step 1 lies in the utilization of LDA in selecting terms with high predictive probability of a specific domain via latent topics, which overcomes the drawbacks of unigram model. Meanwhile, the hierarchical relations among domain terms are exploited by a novel approach based on word association analysis in step 2. The proposed method is tested on two datasets in different languages. The experimental results show that the terms obtained by this method are intuitively relevant to the reference domain and many term pairs with hierarchical relations are discovered. And the relations reflect the structure of the domain rather well. Compared to other approaches, the proposed one is more accurate in both domain terms mining and hierarchical relation learning tasks.
Starting Page	235
Ending Page	240
File Size	672696
Page Count	6
File Format	PDF
ISBN	9781457721342
DOI	10.1109/ICMLA.2011.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Latent Dirichlet Allocation Electronic publishing domain-specific thesaurus Semantics Encyclopedias word association Thesauri Internet Mathematical model term hierarchy
Content Type	Text
Resource Type	Article

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