Title :
Visual Knowledge Reasoning on Typed Categorical Structure
Author :
Wang, Qingquan ; Rong, Lili ; Yu, Kai
Author_Institution :
Inst. of Syst. Eng., Dalian Univ. of Technol., Dalian
Abstract :
Knowledge reasoning is the major content of effective knowledge discovery, because it can facilitate the detection of new knowledge from already known. The visualization of knowledge reasoning is customary to human thinking that needs a graph-based representation to unify structure and logic for higher reasoning capability. Categorical knowledge structures are special method of formalization based on category theory and typed category theory for structured knowledge representation. This paper presents a new reasoning method at an angle of knowledge association and deduction. This method changes basic knowledge reasoning to the computation of categorical structure. This method visualizes the process of knowledge reasoning through analogical functors and categorical pushouts.
Keywords :
category theory; data mining; data visualisation; inference mechanisms; knowledge representation; type theory; analogical functors; categorical knowledge structures; categorical pushouts; graph-based representation; human thinking; knowledge association; knowledge deduction; knowledge discovery; reasoning capability; structured knowledge representation; typed categorical structure; typed category theory; visual knowledge reasoning; Fuzzy systems; Graph theory; Humans; Knowledge engineering; Knowledge management; Knowledge representation; Logic; Mathematics; Systems engineering and theory; Visualization;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Jinan Shandong
Print_ISBN :
978-0-7695-3305-6
DOI :
10.1109/FSKD.2008.294