DocumentCode
2097653
Title
Semantic Text Deep Mining Based on Knowledge Element
Author
Wen, Youkui ; Wen, Hao
Author_Institution
Schools of Econ. & Manage., Univ. of Xidian, Xi´´an, China
fYear
2011
fDate
17-18 Sept. 2011
Firstpage
90
Lastpage
93
Abstract
With the ever-increasing growth of data and information, finding the appropriate knowledge becomes a real challenge and an urgent task. Traditional data and information retrieval systems that support the current web are no longer adequate for knowledge seeking tasks. Knowledge retrieval systems will be the next generation of retrieval systems to serve those purposes. However, the key problem becomes how to construct the basic unit of knowledge retrieval, crossing from data retrieval, information retrieval to knowledge retrieval. From the perspective of knowledge presentation and user needs, the knowledge is a category with context. This paper proposes a semantic text deep mining based on knowledge element. The basic unit of knowledge retrieval and the semantic triangle model of knowledge element are discussed. Application of semantic triangle of knowledge element is given by an example of mining electronic medical records. Experimental results verify the validity and feasibility of the design scheme.
Keywords
data mining; information retrieval; data retrieval; information retrieval systems; knowledge element; knowledge retrieval systems; knowledge seeking tasks; semantic text deep mining; Cognition; Context; Diseases; Hospitals; Hypertension; Semantics; Knowledge retrieval; category theory; knowledge element; semantic triangle;
fLanguage
English
Publisher
ieee
Conference_Titel
Internet Computing & Information Services (ICICIS), 2011 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4577-1561-7
Type
conf
DOI
10.1109/ICICIS.2011.29
Filename
6063200
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