Abstracting Web Agent Proofs into Human-Level Justifications

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Citation: Vasco Furtado and Paulo Pinheiro da Silva and Deborah L. McGuinness and Priyendra Deshwal and Dhyanesh Narayanan and Juliana Carvalho and Vladia Pinheiro and Cynthia Chang. (2007) Abstracting Web Agent Proofs into Human-Level Justifications. In Proceedings of the 20th International FLAIRS Conference (FLAIRS-20), May,2007.

Publication inproceedings ( Edit )
type InProceedings
bibtype inproceedings
Bibtex basics
author Vasco Furtado and Paulo Pinheiro da Silva and Deborah L. McGuinness and Priyendra Deshwal and Dhyanesh Narayanan and Juliana Carvalho and Vladia Pinheiro and Cynthia Chang
title Abstracting Web Agent Proofs into Human-Level Justifications
booktitle Proceedings of the 20th International FLAIRS Conference (FLAIRS-20)
address Key West, Florida
year 2007
month May
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abstract Information supporting answer explanations are derived from proofs. One of the difficulties for humans to understand web agent proofs is that the proofs are typically described at the machine-level. In this paper, we introduce a novel and generic approach for abstracting machine-level portable proofs into human-level justifications. This abstraction facilitates generating explanations from proofs on the web. Our approach consists of creating a repository of proof templates, called abstraction patterns, describing how machine-level inference rules and axioms in proofs can be replaced by rules that are more meaningful for humans. Intermediate results supporting machine-level proofs may also be dropped during the abstraction process.The Inference Web Abstractor algorithm has been developed with the goal of matching the abstraction patterns in the repository against the original proof and applying a set of strategies to abstract the proof thereby simplifying its presentation. The tools used for creating and applying abstraction patterns are shown along with an intelligence analysis example.

KSL Technical Report ID: KSL-07-06
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Abstract Information supporting answer explanations Information supporting answer explanations are derived from proofs. One of the difficulties for humans to understand web agent proofs is that the proofs are typically described at the machine-level. In this paper, we introduce a novel and generic approach for abstracting machine-level portable proofs into human-level justifications. This abstraction facilitates generating explanations from proofs on the web. Our approach consists of creating a repository of proof templates, called abstraction patterns, describing how machine-level inference rules and axioms in proofs can be replaced by rules that are more meaningful for humans. Intermediate results supporting machine-level proofs may also be dropped during the abstraction process.The Inference Web Abstractor algorithm has been developed with the goal of matching the abstraction patterns in the repository against the original proof and applying a set of strategies to abstract the proof thereby simplifying its presentation. The tools used for creating and applying abstraction patterns are shown along with an intelligence analysis example. ong with an intelligence analysis example.
Address Key West, Florida  +
Author Vasco Furtado and Paulo Pinheiro da Silva and Deborah L. McGuinness and Priyendra Deshwal and Dhyanesh Narayanan and Juliana Carvalho and Vladia Pinheiro and Cynthia Chang  +
Bibtype inproceedings  +
Booktitle Proceedings of the 20th International FLAIRS Conference (FLAIRS-20)  +
Has author Vasco Furtado and Paulo Pinheiro da Silva and Deborah L. McGuinness and Priyendra Deshwal and Dhyanesh Narayanan and Juliana Carvalho and Vladia Pinheiro and Cynthia Chang  +
Has identifier KSL-07-06  +
Has publishing details May,2007  +
Has title Abstracting Web Agent Proofs into Human-Level Justifications  +
Has where published Proceedings of the 20th International FLAIRS Conference (FLAIRS-20)  +
Has year 2007  +
Ksl tr id KSL-07-06  +
Month May  +
Process note NO  +
Title Abstracting Web Agent Proofs into Human-Level Justifications  +
Year 2007  +
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