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Probabilistic soft logic

Known as: PSL 
Probabilistic soft logic (PSL) is a framework for collective, probabilistic reasoning in relational domains. PSL uses first order logic rules as a… Expand
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Papers overview

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2016
2016
Lexical inference problem is a significant component of some recent core AI and NLP research problems like machine reading and… Expand
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2016
2016
Global information such as event-event association, and latent local information such as fine-grained entity types, are crucial… Expand
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2015
2015
In this work, we build an entity/event-level sentiment analysis system, which is able to recognize and infer both explicit and… Expand
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Highly Cited
2015
Highly Cited
2015
A fundamental challenge in developing high-impact machine learning technologies is balancing the need to model rich, structured… Expand
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2014
2014
Probabilistic Soft Logic (PSL) is a recently developed framework for probabilistic logic. We use PSL to combine logical and… Expand
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2014
2014
We propose a new approach to semantic parsing that is not constrained by a fixed formal ontology and purely logical inference… Expand
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Highly Cited
2013
Highly Cited
2013
Massive open online courses (MOOCs) attract a large number of student registrations, but recent studies have shown that only a… Expand
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Review
2012
Review
2012
Probabilistic soft logic (PSL) is a framework for collective, probabilistic reasoning in relational domains. PSL uses first order… Expand
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2012
2012
Trust plays a key role in social interactions. Explicitly modeling trust is therefore an important aspect of social network… Expand
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2010
2010
We introduce the concept of a decision-driven model, a probabilistic model that reasons directly over the uncertain information… Expand
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