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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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| 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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Abstract:
Managing large collections of documents is an important problem for many areas of science, industry, and culture. Probabilistic topic modeling offers a promising solution. Topic modeling is an unsupervised machine learning method and the evaluation of this model is an interesting problem on its own. Topic interpretability measures have been developed in recent years as a more natural option for topic quality evaluation, emulating human perception of coherence with word sets correlation scores. In this paper, we show experimental evidence of the improvement of topic coherence score by restricting the training corpus to that of relevant information in the document obtained by Entity Recognition. We experiment with job advertisement data and find that with this approach topic models improve interpretability in about 40 percentage points on average. Our analysis reveals as well that using the extracted text chunks, some redundant topics are joined while others are split into more skill-specific topics. Fine-grained topics observed in models using the whole text are preserved.
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Keyword:
Computational linguistics. Natural language processing; P98-98.5
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URL: https://doaj.org/article/2ad6a44bad3f4267a584ff60fcd19417
https://doi.org/10.2478/pralin-2018-0004
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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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