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The SENSEVAL-3 multilingual English-Hindi lexical sample task
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In: http://www.cs.unt.edu/~rada/papers/chklovski.senseval04.pdf (2004)
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Large-Scale Extraction of FineGrained Semantic Relations between Verbs
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In: http://km.aifb.kit.edu/ws/msw2004/camera/Pantel Large-Scale Extraction of Fine-Grained Semantic.pdf (2004)
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| 3 |
The SENSEVAL-3 Multilingual English-Hindi Lexical Sample Task
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In: http://www.d.umn.edu/~tpederse/Pubs/senseval3-3.pdf (2004)
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BASE
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| 4 |
The Senseval-3 English lexical sample task
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In: http://www.cs.unt.edu/~rada/papers/mihalcea2.senseval04.pdf (2004)
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BASE
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| 5 |
The Senseval-3 English lexical sample task
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In: http://www.cs.unt.edu/~rada/papers/mihalcea2.senseval04.ps (2004)
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BASE
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| 6 |
The SENSEVAL-3 multilingual English-Hindi lexical sample task
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In: http://www.cs.unt.edu/~rada/papers/chklovski.senseval04.ps (2004)
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BASE
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| 7 |
The Senseval-3 English lexical sample task
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In: http://www.kilgarriff.co.uk/Publications/2004-MihalceaChklovskiKilg-SENSEVAL.pdf (2004)
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| 8 |
The Senseval-3 English lexical sample task
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In: http://www.aclweb.org/anthology-new/W/W04/W04-0807.pdf (2004)
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LEARNER: A System for Acquiring Commonsense Knowledge by Analogy
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In: http://www.openmind.org/papers/chklovski2003learner.pdf (2003)
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LEARNER: A System for Acquiring Commonsense Knowledge by Analogy
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In: http://www.cs.xu.edu/%7Egunter/Commonsense.pdf (2003)
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Abstract:
One of the long-term goals of Artificial Intelligence is construction of a machine that is capable of reasoning about the everyday world the way humans are. In this paper, I first argue that construction of a large collec-tion of statements about everyday world (a repository of commonsense knowledge) is a valuable step towards this long-term goal. Then, I point out that volunteer con-tributors over the Internet — a frequently overlooked source of knowledge — can be tapped to construct such a knowledge repository. To operationalize construction of a large commonsense knowledge repository by volun-teer contributors, I then introduce cumulative analogy, a class of analogy-based reasoning algorithms that lever-age existing knowledge to pose knowledge acquisition questions to the volunteer contributors. The algorithms have been implemented and deployed as the Learner system. To date, about 3,400 volunteer contributors have interacted with the system over the course of 11 months, increasing a starting collection of 47,147 state-ments by 362 % to a total of 217,971. The deployed sys-tem and the growing collection of knowledge it acquired are publicly available from
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Keyword:
Analogies; Categories and Subject Descriptors I.2.6 [Learning; commonsense knowledge; Concept learning; Experimentation; Knowl- edge acquisition General Terms Algorithms; Languages Keywords Analogy; volunteer contribu
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URL: http://www.cs.xu.edu/%7Egunter/Commonsense.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.657.1757
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Building a Sense Tagged Corpus with Open Mind Word Expert
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In: http://acl.ldc.upenn.edu/W/W02/W02-0817.pdf (2002)
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Building a Sense Tagged Corpus with Open Mind Word Expert
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In: http://www.utdallas.edu/~rada/papers/acl.wsd.2002.ps (2002)
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