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
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;
Conference_Titel :
Internet Computing & Information Services (ICICIS), 2011 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-1561-7
DOI :
10.1109/ICICIS.2011.29