DBLP:conf/ijcai/MacCartneyMAU03 +, KSL-03-12 + redirect page
Practical Partition-Based Theorem Proving for Large Knowledge Bases + Has identifier
Practical Partition-Based Theorem Proving for Large Knowledge Bases + Ksl tr id
| Practical Partition-Based Theorem Proving for Large Knowledge Bases |
Bibtype
inproceedings
Has publishing details
August,2003
Has title
Practical Partition-Based Theorem Proving for Large Knowledge Bases
Has where published
Proceedings of the Nineteenth International Conference on Artificial Intelligence (IJCAI-03)
Has year
2003
Title
Practical Partition-Based Theorem Proving for Large Knowledge Bases
Year
2003
Abstract
Query answering over commonsense knowledge … Query answering over commonsense knowledge bases typically employs a first-order logic theorem prover. While first-order inference is intractable in general, provers can often be hand-tuned to answer queries with reasonable performance in practice. Appealing to previous theoretical work on partition-based reasoning, we propose resolution-based theorem proving strategies that exploit the structure of a KB to improve the efficiency of reasoning. We analyze and experimentally evaluate these strategies with a testbed based on the SNARK theorem prover. Exploiting graph-based partitioning algorithms, we show how to compute a partition-derived ordering for ordered resolution, with good experimental results, offering an automatic alternative to hand-crafted orderings. We further propose a new resolution strategy, MFS resolution, that combines partition-based message passing with focused sublanguage resolution. Our experiments show a significant reduction in the number of resolution steps when this strategy is used. Finally, we augment partition-based message passing, partition-derived ordering, and MFS by combining them with the set-of-support restriction. While these combinations are incomplete, they often produce dramatic improvements in practice. This work presents promising practical techniques for query answering with large and potentially distributed commonsense KBs. d potentially distributed commonsense KBs.
Author
Bill MacCartney and Sheila A. McIlraith and Eyal Amir and Tomás E. Uribe +
Booktitle
Proceedings of the Nineteenth International Conference on Artificial Intelligence (IJCAI-03) +
Has author
Bill MacCartney and Sheila A. McIlraith and Eyal Amir and Tomás E. Uribe +
Has identifier
Practical Partition-Based Theorem Proving for Large Knowledge Bases +
Ksl tr id
Practical Partition-Based Theorem Proving for Large Knowledge Bases +
Month
August +
Process note
NO +
Categories InProceedings +, KSL Technical Report +, Publication +
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