Machine Translation Evaluation Meets Community Question Answering

December 06, 2019 ยท Declared Dead ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

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Authors Francisco Guzmรกn, Lluรญs Mร rquez, Preslav Nakov arXiv ID 1912.02998 Category cs.CL: Computation & Language Cross-listed cs.IR, cs.LG Citations 29 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 4 months ago
Abstract
We explore the applicability of machine translation evaluation (MTE) methods to a very different problem: answer ranking in community Question Answering. In particular, we adopt a pairwise neural network (NN) architecture, which incorporates MTE features, as well as rich syntactic and semantic embeddings, and which efficiently models complex non-linear interactions. The evaluation results show state-of-the-art performance, with sizeable contribution from both the MTE features and from the pairwise NN architecture.
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