| 1 |
Distributional Semantic Models for English verbs and nouns ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 2 |
The Role of negative information when learning dense word vectors ; O papel da informação negativa na aprendizagem de vetores palavra densos
|
|
|
|
BASE
|
|
Show details
|
|
|
| 3 |
Word Representations Concentrate and This is Good News!
|
|
|
|
In: CoNLL 2020 - 24th Conference on Computational Natural Language Learning ; https://hal.univ-grenoble-alpes.fr/hal-03356609 ; CoNLL 2020 - 24th Conference on Computational Natural Language Learning, Association for Computational Linguistics (ACL), Nov 2020, Online, France. pp.325-334, ⟨10.18653/v1/2020.conll-1.25⟩ (2020)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
Can word vectors help corpus linguists? ; Les vecteurs lexicaux peuvent-ils venir en aide aux linguistes de corpus ?
|
|
|
|
In: ISSN: 0039-3274 ; Studia Neophilologica ; https://halshs.archives-ouvertes.fr/halshs-01657591 ; Studia Neophilologica, Taylor & Francis (Routledge): SSH Titles, 2019, ⟨10.1080/00393274.2019.1616220⟩ (2019)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
Better Word Representation Vectors Using Syllabic Alphabet: A Case Study of Swahili
|
|
|
|
In: Applied Sciences ; Volume 9 ; Issue 18 (2019)
|
|
Abstract:
Deep learning has extensively been used in natural language processing with sub-word representation vectors playing a critical role. However, this cannot be said of Swahili, which is a low resource and widely spoken language in East and Central Africa. This study proposed novel word embeddings from syllable embeddings (WEFSE) for Swahili to address the concern of word representation for agglutinative and syllabic-based languages. Inspired by the learning methodology of Swahili in beginner classes, we encoded respective syllables instead of characters, character n-grams or morphemes of words and generated quality word embeddings using a convolutional neural network. The quality of WEFSE was demonstrated by the state-of-art results in the syllable-aware language model on both the small dataset (31.229 perplexity value) and the medium dataset (45.859 perplexity value), outperforming character-aware language models. We further evaluated the word embeddings using word analogy task. To the best of our knowledge, syllabic alphabets have not been used to compose the word representation vectors. Therefore, the main contributions of the study are a syllabic alphabet, WEFSE, a syllabic-aware language model and a word analogy dataset for Swahili.
|
|
Keyword:
deep learning; perplexity; syllabic alphabet; syllable-aware language model; word analogy; word representation vectors
|
|
URL: https://doi.org/10.3390/app9183648
|
|
BASE
|
|
Hide details
|
|
|
| 6 |
RedMed: Extending drug lexicons for social media applications ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 7 |
RedMed: Extending drug lexicons for social media applications ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Sparse distributed representations as word embeddings for language understanding
|
|
|
|
BASE
|
|
Show details
|
|
|
| 9 |
Using EEG to decode semantics during an artificial language learning task
|
|
|
|
BASE
|
|
Show details
|
|
|
| 10 |
Construction grammars: the empirical challenge ; Les grammaires de constructions à l'épreuve de l'empirie
|
|
|
|
In: https://halshs.archives-ouvertes.fr/tel-01657598 ; Linguistique. Université Paris Diderot (Paris 7), 2016 (2016)
|
|
BASE
|
|
Show details
|
|
|
| 11 |
A Statistical Approach to Retrieving Historical Manuscript Images without Recognition
|
|
|
|
In: DTIC (2003)
|
|
BASE
|
|
Show details
|
|
|
| 12 |
disambiguation
|
|
|
|
In: http://lexicometrica.univ-paris3.fr/jadt/jadt2012/Communications/Maldonado-Guerra+et+al.+-+First-order+and+second-order+context+representations.pdf
|
|
BASE
|
|
Show details
|
|
|
| 13 |
Use of Semantic Relation Between Words in Text Clustering
|
|
|
|
In: http://www.cse.iitb.ac.in/~pb/papers/cluster_unl.pdf
|
|
BASE
|
|
Show details
|
|
|
|
|
