TY - GEN
T1 - A multi-level text representation model within background knowledge based on human cognitive process
AU - Zhang, Jun
AU - Li, Qing
AU - Luo, Xiangfeng
AU - Wei, Xiao
PY - 2013/12/9
Y1 - 2013/12/9
N2 - Text representation is one of the most fundamental works in text comprehension, processing, and search. Various works have been proposed to mine the semantics in texts and then to represent them. However, most of them only focus on how to mine semantics from the text itself while the background knowledge, which is very important to text understanding, is not taken into consideration. In this paper, on the basis of human cognitive process, we propose a multi-level text representation model within background knowledge, called TRMBK. It is composed of three levels, which are machine surface code (MSC), machine text base (MTB) and machine situational model (MSM). All of the three are able to be automatically constructed to acquire semantics both inside and outside of the text. Simultaneously, we also propose a method to automatically establish background knowledge and offer supports for the current text comprehension. Finally, experiments and comparisons have been presented to show the better performance of TRMBK.
AB - Text representation is one of the most fundamental works in text comprehension, processing, and search. Various works have been proposed to mine the semantics in texts and then to represent them. However, most of them only focus on how to mine semantics from the text itself while the background knowledge, which is very important to text understanding, is not taken into consideration. In this paper, on the basis of human cognitive process, we propose a multi-level text representation model within background knowledge, called TRMBK. It is composed of three levels, which are machine surface code (MSC), machine text base (MTB) and machine situational model (MSM). All of the three are able to be automatically constructed to acquire semantics both inside and outside of the text. Simultaneously, we also propose a method to automatically establish background knowledge and offer supports for the current text comprehension. Finally, experiments and comparisons have been presented to show the better performance of TRMBK.
KW - Background knowledge
KW - Human cognitive process
KW - Semantics
KW - Situational model
KW - Surface code
KW - Text base
KW - Text comprehension
KW - Text representation
UR - http://www.scopus.com/inward/record.url?scp=84889019189&partnerID=8YFLogxK
U2 - 10.1109/ICCI-CC.2013.6622262
DO - 10.1109/ICCI-CC.2013.6622262
M3 - Conference article published in proceeding or book
AN - SCOPUS:84889019189
SN - 9781479907816
T3 - Proceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013
SP - 324
EP - 331
BT - Proceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013
T2 - 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013
Y2 - 16 July 2013 through 18 July 2013
ER -