TY - GEN
T1 - Feature matrix models for information extraction
AU - Dong, Hua
AU - Fang, Liu
AU - Dechang, Chen
PY - 2005
Y1 - 2005
N2 - To extract useful information which really contribute to the target issue from huge amounts of data or text description is an important task towards a number of research fields (e.g., genomics study and text mining). In this paper, a general feature matrix model (FMM) is proposed aiming to provide partial answer to this task. Specifically, one instantiation of FMM is used for identifying feature genes based on microarray data, and the other for extracting information according to case description.
AB - To extract useful information which really contribute to the target issue from huge amounts of data or text description is an important task towards a number of research fields (e.g., genomics study and text mining). In this paper, a general feature matrix model (FMM) is proposed aiming to provide partial answer to this task. Specifically, one instantiation of FMM is used for identifying feature genes based on microarray data, and the other for extracting information according to case description.
KW - Feature matrix model
KW - Information extraction
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=60749084754&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:60749084754
SN - 9781932415797
T3 - Proceedings of the 2005 International Conference on Data Mining, DMIN'05
SP - 229
EP - 235
BT - Proceedings of the 2005 International Conference on Data Mining, DMIN'05
T2 - 2005 International Conference on Data Mining, DMIN'05
Y2 - 20 June 2005 through 23 June 2005
ER -