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Distributional Semantics and Kernels

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If you have a question about this talk, please contact Ekaterina Kochmar.

This talk will cover some of my work which combines distributional models of lexical semantics with kernel methods. I will be talking how combinations of models can be used to improve kernel classification. In particular, I will talk about the use of HAL and BEAGLE lexical co-occurrence models and how they can be incorporated into a multiple kernel learning framework to improve identification of protein-protein interaction sentences. Conversely, I will be talking about the ways one can use kernel combinations to introduce inter-document similarity into Explicit Semantic Analysis.

This talk is part of the NLIP Seminar Series series.

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