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"The Latent Relation Mapping Engine: Algorithm and Experiments"^^ .
"Many AI researchers and cognitive scientists have argued that analogy is the core of cognition. The most influential work on computational modeling of analogy-making is Structure Mapping Theory (SMT) and its implementation in the Structure Mapping Engine (SME). A limitation of SME is the requirement for complex hand-coded representations. We introduce the Latent Relation Mapping Engine (LRME), which combines ideas from SME and Latent Relational Analysis (LRA) in order to remove the requirement for hand-coded representations. LRME builds analogical mappings between lists of words, using a large corpus of raw text to automatically discover the semantic relations among the words. We evaluate LRME on a set of twenty analogical mapping problems, ten based on scientific analogies and ten based on common metaphors. LRME achieves human-level performance on the twenty problems. We compare LRME with a variety of alternative approaches and find that they are not able to reach the same level of performance."^^ .
"2008-12-22" .
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"33" .
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"AI Access Foundation"^^ .
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"Journal of Artificial Intelligence Research"^^ .
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"Peter D."^^ .
"Turney"^^ .
"Peter D. Turney"^^ .
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"The Latent Relation Mapping Engine: Algorithm and Experiments (PDF)"^^ .
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"NRC-50738.pdf"^^ .
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"The Latent Relation Mapping Engine: Algorithm and Experiments (Image (PNG))"^^ .
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"preview.png"^^ .
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"The Latent Relation Mapping Engine: Algorithm and Experiments (Indexer Terms)"^^ .
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"indexcodes.txt"^^ .
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"HTML Summary of #6305 \n\nThe Latent Relation Mapping Engine: Algorithm and Experiments\n\n" .
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"Language" .
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"Computational Linguistics" .
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"Semantics" .
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"Machine Learning" .
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"Artificial Intelligence" .
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