Deep Context Resolution
Abstract
Conversations depend on information from the context. To go beyond
one-round conversation, a chatbot must resolve contextual information such as:
1) co-reference resolution, 2) ellipsis resolution,
and 3) conjunctive relationship resolution.
There are simply not enough data to avoid these problems by trying to train a sequence-to-sequence
model for multi-round conversation similar to that of one-round conversation.
The contributions of this paper are: 1) We formulate the problem of
context resolution for conversation;
2) We present deep learning models, including
an end-to-end network for context resolution;
3) We propose a way of creating a huge amount of
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Cite this version of the work
Junnan Chen
(2018).
Deep Context Resolution. UWSpace.
http://hdl.handle.net/10012/13301
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