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Capability modeling of knowledge-based agents for commonsense knowledge integration
Abstract Robust intelligent systems require commonsRobust intelligent systems require commonsense knowledge. While significant progress has been made in building large commonsense knowledge bases, they are intrinsically incomplete. It is difficult to combine multiple knowledge bases due to their different choices of representation and inference mechanisms, thereby limiting users to one knowledge base and its reasonable methods for any specific task. This paper presents a multi-agent framework for commonsense knowledge integration, and proposes an approach to capability modeling of knowledge bases without a common ontology. The proposed capability model provides a general description of large heterogeneous knowledge bases, such that contents accessible by the knowledge-based agents may be matched up against specific requests. The concept correlation matrix of a knowledge base is transformed into a k-dimensional vector space using low-rank approximation for dimensionality reduction. Experiments are performed with the matchmaking mechanism for commonsense knowledge integration framework using the capability models of ConceptNet, WordNet, and Wikipedia. In the user study, the matchmaking results are compared with the ranked lists produced by online users to show that over 85% of them are accurate and have positive correlation with the user-produced ranked lists.ation with the user-produced ranked lists.
Abstractsub Robust intelligent systems require commonsRobust intelligent systems require commonsense knowledge. While significant progress has been made in building large commonsense knowledge bases, they are intrinsically incomplete. It is difficult to combine multiple knowledge bases due to their different choices of representation and inference mechanisms, thereby limiting users to one knowledge base and its reasonable methods for any specific task. This paper presents a multi-agent framework for commonsense knowledge integration, and proposes an approach to capability modeling of knowledge bases without a common ontology. The proposed capability model provides a general description of large heterogeneous knowledge bases, such that contents accessible by the knowledge-based agents may be matched up against specific requests. The concept correlation matrix of a knowledge base is transformed into a k-dimensional vector space using low-rank approximation for dimensionality reduction. Experiments are performed with the matchmaking mechanism for commonsense knowledge integration framework using the capability models of ConceptNet, WordNet, and Wikipedia. In the user study, the matchmaking results are compared with the ranked lists produced by online users to show that over 85% of them are accurate and have positive correlation with the user-produced ranked lists.ation with the user-produced ranked lists.
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-25044-6_24  +
Has author Kuo Y.-L. + , Hsu J.Y.-J. +
Has extra keyword Capability model + , Common sense + , Commonsense knowledge + , Commonsense knowledge basis + , Concept correlation + , Dimensionality reduction + , General description + , Heterogeneous Knowledge + , In-buildings + , Inference mechanism + , Knowledge base + , Knowledge basis + , Low rank approximations + , Multiagent framework + , Online users + , Positive correlations + , Specific tasks + , User study + , Wikipedia + , Wordnet + , Data privacy + , Integration + , Intelligent systems + , Knowledge based systems + , Knowledge representation + , Multi agent systems + , Network security + , Ontology + , Vector spaces + , Intelligent agents +
Has keyword Agent description + , Capability model + , Common sense + , Commonsense knowledge integration + , Multi-agent system +
Isbn 9783642250439  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 299–310  +
Published in Lecture Notes in Computer Science +
Title Capability modeling of knowledge-based agents for commonsense knowledge integration +
Type conference paper  +
Volume 7047 LNAI  +
Year 2011 +
Creation dateThis property is a special property in this wiki. 7 November 2014 11:49:08  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 11:49:08  +
DateThis property is a special property in this wiki. 2011  +
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