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        <title>Improving Semantic Composition with Offset Inference</title>
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        <namePart type="family">Weeds</namePart>
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            <title>Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</title>
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            <namePart type="given">Min-Yen</namePart>
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    <abstract>Count-based distributional semantic models suffer from sparsity due to unobserved but plausible co-occurrences in any text collection. This problem is amplified for models like Anchored Packed Trees (APTs), that take the grammatical type of a co-occurrence into account. We therefore introduce a novel form of distributional inference that exploits the rich type structure in APTs and infers missing data by the same mechanism that is used for semantic composition.</abstract>
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    <identifier type="doi">10.18653/v1/P17-2069</identifier>
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%0 Conference Proceedings
%T Improving Semantic Composition with Offset Inference
%A Kober, Thomas
%A Weeds, Julie
%A Reffin, Jeremy
%A Weir, David
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F kober-etal-2017-improving
%X Count-based distributional semantic models suffer from sparsity due to unobserved but plausible co-occurrences in any text collection. This problem is amplified for models like Anchored Packed Trees (APTs), that take the grammatical type of a co-occurrence into account. We therefore introduce a novel form of distributional inference that exploits the rich type structure in APTs and infers missing data by the same mechanism that is used for semantic composition.
%R 10.18653/v1/P17-2069
%U https://aclanthology.org/P17-2069
%U https://doi.org/10.18653/v1/P17-2069
%P 433-440

Markdown (Informal)

[Improving Semantic Composition with Offset Inference](https://aclanthology.org/P17-2069) (Kober et al., ACL 2017)

• Improving Semantic Composition with Offset Inference (Kober et al., ACL 2017)

ACL

• Thomas Kober, Julie Weeds, Jeremy Reffin, and David Weir. 2017. Improving Semantic Composition with Offset Inference. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 433–440, Vancouver, Canada. Association for Computational Linguistics.