Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Implementing a semantic interpreter using conceptual graphs
IBM Journal of Research and Development
Conceptual graphs for the analysis and generation of sentences
IBM Journal of Research and Development
Automatic labeling of semantic roles
Computational Linguistics
Class-Based Construction of a Verb Lexicon
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
A fully statistical approach to natural language interfaces
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Automatic labeling of semantic roles
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Graph-based text representation and knowledge discovery
Proceedings of the 2007 ACM symposium on Applied computing
Text clustering algorithm based on spectral graph seriation
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Information retrieval with a simplified conceptual graph-like representation
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
A method for efficient malicious code detection based on conceptual similarity
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part IV
Detection of unknown malicious script code using a conceptual graph and SVM
Proceedings of the 2012 ACM Research in Applied Computation Symposium
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This paper describes a system for constructing conceptual graph representation of text by using a combination of existing linguistic resources (VerbNet and WordNet). We use a two-step approach, by firstly identifying the semantic roles in a sentence, and then using these roles, together with semi-automatically compiled domain-specific knowledge to construct the conceptual graph representation.