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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