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Chinese character decomposition for neural MT with multi-word expressions
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In: Han, Lifeng orcid:0000-0002-3221-2185 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 , Smeaton, Alan F. orcid:0000-0003-1028-8389 and Bolzoni, Paolo (2021) Chinese character decomposition for neural MT with multi-word expressions. In: 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021), 31 May- 2 June 2021, Reykjavik, Iceland (Online). (In Press) (2021)
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Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
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One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets ...
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Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ...
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InFillmore: Frame-Guided Language Generation with Bidirectional Context ...
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Learning Embeddings for Rare Words Leveraging Internet Search Engine and Spatial Location Relationships ...
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Evaluating Universal Dependency Parser Recovery of Predicate Argument Structure via CompChain Analysis ...
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ParsFEVER : a Dataset for Farsi Fact Extraction and Verification ...
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Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge ...
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Teach the Rules, Provide the Facts: Targeted Relational-knowledge Enhancement for Textual Inference ...
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Multilingual Neural Semantic Parsing for Low-Resourced Languages ...
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Inducing Language-Agnostic Multilingual Representations ...
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Denoising Word Embeddings by Averaging in a Shared Space ...
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Consistency improvement with a feedback recommendation in personalized linguistic group decision making
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Abstract:
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. ; Consistency is an important issue in linguistic decision making with various consistency measures and consistency improving methods available in the literature. However, existing linguistic consistency studies omit the fact that words mean different things for different people, that is, decision makers' personalized individual semantics (PISs) over their expressed linguistic preferences are ignored. Therefore, the aim of this article is to propose a novel consistency improving approach based on PISs in linguistic group decision making. The proposed approach combines the characteristics of personalized representation and integrates the PIS-based model in measuring and improving the consistency of linguistic preference relations. A detailed numerical and comparative analysis to support the feasibility of the proposed approach is provided.
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Keyword:
Additives; Computational modeling; Decision making; Linguistics; Numerical models; Semantics
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URL: https://dora.dmu.ac.uk/handle/2086/21231 https://doi.org/10.1109/tcyb.2021.3085760
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Evaluating a Joint Training Approach for Learning Cross-lingual Embeddings with Sub-word Information without Parallel Corpora on Lower-resource Languages ...
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Can Transformer Langauge Models Predict Psychometric Properties? ...
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Braiding Language (by Computer): Lushootseed Grammar Engineering
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