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We propose a framework for inferring the latent attitudes or preferences of users by performing probabilistic first-order logical reasoning over the social network graph.
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W. Y. Wang, K. Mazaitis, and W. W. Cohen · 2013
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I. Beltagy, K. Erk, and R. Mooney · 2014
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B. Goertzel, C. Pennachin, and N. Geisweiller · 2014
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J. Li and C. Cardie · 2014
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J. Li, A. Ritter, C. Cardie, and E. Hovy · 2014
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Weakly supervised user profile extraction from twitter
J. Li, A. Ritter, and E. Hovy · 2014
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Proppr: Efficient first-order probabilistic logic programming for structure discovery, parameter learning, and scalable inference
W. Y. Wang, K. Mazaitis, and W. W. Cohen · 2014
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Structure learning via parameter learning
W. Y. Wang, K. Mazaitis, and W. W. Cohen · 2014
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Efficient inference and learning in a large knowledge base: Reasoning with extracted information using a locally groundable first-order probabilistic logic
W. Y. Wang, K. Mazaitis, N. Lao, T. Mitchell, and W. W. Cohen · 2014
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