Latest revision as of 17:04, 3 February 2021

Abstract

hough deep neural networks have been proving to be excellent tools to deliver state-of-the-art results, when data is scarce and the tackled tasks involve complex semantic inference, deep linguistic processing and traditional structure-based approaches, such as tree kernel methods, are an alternative solution. Community Question Answering is a research area that benefits from deep linguistic analysis to improve the experience of the community of forum users. In this paper, we present a UIMA framework to distribute the computation of cQA tasks over computer clusters such that traditional systems can scale to large datasets and deliver fast processing.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.18653/v1/p18-4023 under the license https://creativecommons.org/licenses/by

• http://hdl.handle.net/11585/709255

• https://www.aclweb.org/anthology/P18-4023.pdf

• https://dblp.uni-trier.de/db/conf/acl/acl2018-4.html#RomeoMBM18,

https://www.aclweb.org/anthology/P18-4023,

https://www.aclweb.org/anthology/P18-4023.pdf,

https://aclanthology.coli.uni-saarland.de/papers/P18-4023/p18-4023,

https://academic.microsoft.com/#/detail/2805001960 under the license cc-by

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