Title :
A novel algebra to articulate feature in text dimension reduction
Author :
Xin Guo ; Yang Xiang ; Qian Chen
Author_Institution :
Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai, China
Abstract :
Challenges in text mining arise from multi-corpus and high dimensionality involving natural language. Features from datasets needs to be composed or articulated. This paper aims to develop a new approach to align text feature using ontology, which can form the base of text dimension reduction. Firstly, a novel text feature graph is defined, based on which we can do articulation. Secondly, an algebra system is proposed for text feature graph computing. Finally, an instance is demonstrated to show the efficiency and accuracy of the proposed approach.
Keywords :
algebra; data mining; natural language processing; ontologies (artificial intelligence); text analysis; algebra system; datasets; high dimensionality; multicorpus; natural language; ontology; text dimension reduction; text feature graph computing; text mining; Algebra; Computers; Educational institutions; Ontologies; Principal component analysis; Semantics; Text mining; algebra system; feature articulation; text dimension reduction;
Conference_Titel :
Granular Computing (GrC), 2013 IEEE International Conference on
Conference_Location :
Beijing
DOI :
10.1109/GrC.2013.6740394