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Hits 2.581 – 2.596 of 2.596
| 2581 |
Metaphor: A Computational Perspective
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In: Computational Linguistics, Vol 44, Iss 1, Pp 191-192 (2018) (2018)
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| 2582 |
We Usually Don’t Like Going to the Dentist: Using Common Sense to Detect Irony on Twitter
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In: Computational Linguistics, Vol 44, Iss 4, Pp 793-832 (2018) (2018)
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| 2583 |
Weighted DAG Automata for Semantic Graphs
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In: Computational Linguistics, Vol 44, Iss 1, Pp 119-186 (2018) (2018)
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| 2584 |
Bayesian Analysis in Natural Language Processing
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In: Computational Linguistics, Vol 44, Iss 1, Pp 187-189 (2018) (2018)
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| 2585 |
Using Tectogrammatical Annotation for Studying Actors and Actions in Sallust’s Bellum Catilinae
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In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 5-28 (2018) (2018)
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| 2586 |
PanParser: a Modular Implementation for Efficient Transition-Based Dependency Parsing
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In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 57-86 (2018) (2018)
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| 2587 |
An Easily Extensible HMM Word Aligner
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In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 87-96 (2018) (2018)
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Abstract:
In this paper, we present a new word aligner with built-in support for alignment types, as well as comparisons between various models and existing aligner systems. It is an open source software that can be easily extended to use models of users’ own design. We expect it to suffice the academics as well as scientists working in the industry to do word alignment, as well as experimenting on their own new models. Here in the present paper, the basic designs and structures will be introduced. Examples and demos of the system are also provided.
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Keyword:
Computational linguistics. Natural language processing; P98-98.5
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URL: https://doaj.org/article/1af0f374b4df496d87f0106c3c100401
https://doi.org/10.2478/pralin-2018-0008
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| 2588 |
Open Source Toolkit for Speech to Text Translation
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In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 125-135 (2018) (2018)
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| 2589 |
Enriching VALLEX with Light Verbs: From Theory to Data and Back Again
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In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 29-56 (2018) (2018)
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| 2590 |
Search for the Relation of Form and Function Using the ForFun Database
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In: Prague Bulletin of Mathematical Linguistics , Vol 110, Iss 1, Pp 71-84 (2018) (2018)
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| 2591 |
Improving Topic Coherence Using Entity Extraction Denoising
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In: Prague Bulletin of Mathematical Linguistics , Vol 110, Iss 1, Pp 85-101 (2018) (2018)
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| 2592 |
A Probabilistic Approach to Error Detection&Correction for Tree-Mapping Grammars
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In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 97-112 (2018) (2018)
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| 2593 |
NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning
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In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 113-124 (2018) (2018)
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| 2594 |
Training Tips for the Transformer Model
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In: Prague Bulletin of Mathematical Linguistics , Vol 110, Iss 1, Pp 43-70 (2018) (2018)
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| 2595 |
Modelling Morphographemic Alternations in Derivation of Czech
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In: Prague Bulletin of Mathematical Linguistics , Vol 110, Iss 1, Pp 7-42 (2018) (2018)
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| 2596 |
Phylogeny in Phonology: How Tai Sound Systems Encode Their Past
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In: Proceedings of the Annual Meetings on Phonology; Proceedings of the 2017 Annual Meeting on Phonology ; 2377-3324 (2018)
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