TY - GEN
T1 - Use of background knowledge in natural language understanding for information fusion
AU - Shapiro, Stuart C.
AU - Schlegel, Daniel R.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/14
Y1 - 2015/9/14
N2 - Tractor is a system for understanding English messages within the context of hard and soft information fusion for situation assessment. Tractor processes a message through text processors, and stores the result, expressed in a formal knowledge representation language, in a syntactic knowledge base. This knowledge base is enhanced with ontological and geographic information. Finally, Tractor applies hand-crafted syntax-semantics mapping rules to convert the enhanced syntactic knowledge base into a semantic knowledge base containing the information from the message enhanced with relevant background information. Throughout its processing, Tractor makes use of various kinds of background knowledge: knowledge of English usage; world knowledge; domain knowledge; and axiomatic knowledge. In this paper, we discuss the various kinds of background knowledge Tractor uses, and the roles they play in Tractor's understanding of the messages.
AB - Tractor is a system for understanding English messages within the context of hard and soft information fusion for situation assessment. Tractor processes a message through text processors, and stores the result, expressed in a formal knowledge representation language, in a syntactic knowledge base. This knowledge base is enhanced with ontological and geographic information. Finally, Tractor applies hand-crafted syntax-semantics mapping rules to convert the enhanced syntactic knowledge base into a semantic knowledge base containing the information from the message enhanced with relevant background information. Throughout its processing, Tractor makes use of various kinds of background knowledge: knowledge of English usage; world knowledge; domain knowledge; and axiomatic knowledge. In this paper, we discuss the various kinds of background knowledge Tractor uses, and the roles they play in Tractor's understanding of the messages.
KW - background knowledge
KW - hard+soft information fusion
KW - information extraction
KW - message understanding
KW - natural language understanding
KW - soft information fusion
UR - https://www.scopus.com/pages/publications/84960473531
M3 - Conference contribution
AN - SCOPUS:84960473531
T3 - 2015 18th International Conference on Information Fusion, Fusion 2015
SP - 901
EP - 907
BT - 2015 18th International Conference on Information Fusion, Fusion 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th International Conference on Information Fusion, Fusion 2015
Y2 - 6 July 2015 through 9 July 2015
ER -