A noisy-channel approach to question answering
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TL;DR
This work introduces a probabilistic noisy-channel model for question answering and shows how it can be exploited in the context of an end-to-end QA system, and shows that the model is flexible enough to accommodate within one mathematical framework many QA-specific resources and techniques.
Abstract
We introduce a probabilistic noisy-channel model for question answering and we show how it can be exploited in the context of an end-to-end QA system. Our noisy-channel system outperforms a state-of-the-art rule-based QA system that uses similar resources. We also show that the model we propose is flexible enough to accommodate within one mathematical framework many QA-specific resources and techniques, which range from the exploitation of WordNet, structured, and semi-structured databases to reasoning, and paraphrasing.
