Computational frameworks for semantic analysis and wikification
Dan Roth · 2013
Computational approaches to problems in Natural Language Understanding and Information Extraction are often modeled as structured predictions - predictions that involve assigning values to sets of interdependent variables. Over the last few years, one of the most successful approaches to studying these problems involves Constrained Conditional Models (CCMs), an Integer Learning Programming formulation that augments probabilistic models with declarative constraints as a way to support such decisions.