The society of mind
CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
WordNet: a lexical database for English
Communications of the ACM
Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace
Autonomous Agents and Multi-Agent Systems
Open Mind Common Sense: Knowledge Acquisition from the General Public
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Multi-agent Architecture for Knowledge Fusion from Distributed Sources
CEEMAS '01 Revised Papers from the Second International Workshop of Central and Eastern Europe on Multi-Agent Systems: From Theory to Practice in Multi-Agent Systems
GOOSE: A Goal-Oriented Search Engine with Commonsense
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Extracting and evaluating general world knowledge from the Brown corpus
HLT-NAACL-TEXTMEANING '03 Proceedings of the HLT-NAACL 2003 workshop on Text meaning - Volume 9
Methods for domain-independent information extraction from the web: an experimental comparison
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
WordNet: similarity - measuring the relatedness of concepts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
WikiRelate! computing semantic relatedness using wikipedia
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Community-based game design: experiments on social games for commonsense data collection
Proceedings of the ACM SIGKDD Workshop on Human Computation
AnalogySpace: reducing the dimensionality of common sense knowledge
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Planning for Reasoning with Multiple Common Sense Knowledge Bases
ACM Transactions on Interactive Intelligent Systems (TiiS) - Special Issue on Common Sense for Interactive Systems
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Robust 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.