[Purpose/significance] In the process of constructing large-scale knowledge base, the manual-based construction approach is lack of efficiency and flexibility. Automatically extracting of massive knowledge from online encyclopedia has attracted attention of an increasing number of scholars. Current research mainly focuses on extracting the data from English online encyclopedia, whereas research about knowledge extraction from Chinese or other languages' data sources is rare.[Method/process] This paper proposes an automatic construction scheme for large-scale knowledge base based on Chinese online Encyclopedia. (i)In the first stage of the scheme, self-expanded learning is performed on the semantic relations between subjects and objects among the knowledge triples. (ii)In the second stage, the semantic relationship between marked attributes and their entities is predicted based on Conditional Random Fields (CRFs) and Support Vector Machine (SVM) classifier.[Result/conclusion] A large-scale knowledge base is automatically constructed based on the scheme, and the experiment results indicate that the scheme possesses feasibility and effectiveness.
Wang Ting
,
Ji Fujun
,
Xu Tiansheng
. A Novel Knowledge Extraction Approach Oriented on Unstructured Information of Chinese Online Encyclopedia[J]. Library and Information Service, 2016
, 60(13)
: 126
-133
.
DOI: 10.13266/j.issn.0252-3116.2016.13.016
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