User generated content oriented Chinese taxonomy construction

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

The taxonomy is one of the basic components in knowledge graphs as it establishes types of classes and semantic relations among the classes. Taxonomies are normally constructed either manually, or by language-dependent rules or patterns for type and relation extraction or inference. Existing work on building taxonomies for knowledge graphs is mostly in English language environment. In this paper, we propose a novel approach for large-scale Chinese taxonomy construction based on user generated content. We take Chinese Wikipedia as the data source, develop methods to extract classes and their relations mined from user tagged categories, and build up the taxonomy using a bottom-up strategy. The algorithms can be easily applied to other Wiki-style data sources. The experiments show that the constructed Chinese taxonomy achieves better results in both quality and quantity.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 17th Asia-PacificWeb Conference,APWeb 2015, Proceedings
EditorsReynold Cheng, Bin Cui, Zhenjie Zhang, Ruichu Cai, Jia Xu
PublisherSpringer Verlag
Pages623-634
Number of pages12
ISBN (Print)9783319252544
DOIs
StatePublished - 2015
Event17th Asia-PacificWeb Conference, APWeb 2015 - Guangzhou, China
Duration: 18 Sep 201520 Sep 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9313
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th Asia-PacificWeb Conference, APWeb 2015
Country/TerritoryChina
CityGuangzhou
Period18/09/1520/09/15

Keywords

  • Knowledge graph
  • Taxonomy
  • Wikipedia

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