Cited by 825Natural Language Processing TechniquesTopic ModelingSpeech Recognition and Synthesis

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Neural Network Methods for Natural Language Processing

Goldberg, Yoav·2017·Synthesis Lectures on Human Language Technologies

DOI 10.1007/978-3-031-02165-7

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Visually imperceptible adversarial patch attacks
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Background
Supporting Argumentation Dialogues in Group Decision Support Systems: An Approach Based on Dynamic Clustering
Conceição, L., Rodrigues, V., Meira, J., Marreiros, G., & Nováis, P. (2022) · Applied Sciences · doi:10.3390/app122110893 · Cited by 5
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Method
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“A language model can predict the next word in the sequence given the words that precede it (Goldberg and Hirst, 2017), which requires it to capture the context of the text.”
Background
A Deep Learning Approach for Negation Detection from Product Reviews written in Spanish
Montenegro, O., Pabón, O. S., & Reyes, R. E. G. D. P. (2021) · Latin American Computer Conference (CLEI) · doi:10.1109/clei53233.2021.9640190 · Cited by 6
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An Experimental Analysis of Multi-Perspective Convolutional Neural Networks
Tu, Z. (2018) · UWSpace (University of Waterloo) · Cited by 4
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Bassett, R., Graves, M., & Reilly, P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.12454 · Cited by 4
Crisis Communication and Computational Methods
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“Over the past decade, significant progress in Artificial Intelligence (AI) has had a transformative impact on diverse fields, such as machine vision [1], robotics [2], and natural language processing [3].”
Background
A Comparative Analysis of Convolutional Neural Networks, Bi-Directional Gated Recurrent Units, and Bi-Directional Long Short-Term Memory for Sequential Data Processing Using Human Emotions Dataset
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“A vocabulary is a word-to-index mapping that allows us to reference the word with their integer representation [17], since machine learning models do not understand words [21].”
Influential
Development of Different Word Vectors and Testing Using Text Classification Algorithms for Telugu
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Advances in monolingual and crosslingual automatic disability annotation in Spanish
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EVALUATING OF EFFICACY SEMANTIC SIMILARITY METHODS FOR COMPARISON OF ACADEMIC THESIS AND DISSERTATION TEXTS
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“NLP techniques can be used for a variety of applications (Goldberg, 2017), including • Semantic analysis: a broad term that encompasses various NLP techniques for analysing the meaning of natural language texts • Sentiment analysis: determining the sentiment (positive, negative, neutral) of a piece of text • Named ent…”
Background
Low-latency full precision optical convolutional neural network accelerator
Jahannia, B., Ye, J., Altaleb, S., Peserico, N., Asadizanjani, N., Heidari, E., Sorger, V. J., & Dalir, H. (2024) · AI and Optical Data Sciences · doi:10.1117/12.3003314 · Cited by 3
Urdu Sentential Paraphrased Plagiarism Detection Using Large Language Models
Iqbal, H. R., Sharjeel, M., Shafi, J., Mehmood, U., & Raza, A. A. (2025) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3748320 · Cited by 3
Machine Learning Models
Savoy, J. (2020) · Springer eBooks · doi:10.1007/978-3-030-53360-1_6 · Cited by 5
A Short-Patterning of the Texts Attributed to Al Ghazali: A “Twitter Look” at the Problem
Volkovich, Z. (2020) · Mathematics · doi:10.3390/math8111937 · Cited by 3
Soft Computing based Clustering Protocols in IoT for Precision and Smart Agriculture: A Survey.
Vatan, & Goyal, S. K. (2021) · Cited by 3
Probing with Noise: Unpicking the Warp and Weft of Embeddings
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Detecting Twitter posts with Adverse Drug Reactions using Convolutional Neural Networks.
Jain, S., Peng, X., & Wallace, B. (2017) · Cited by 3
Sub-label dependencies for neural morphological tagging--the joint submission of University of Colorado and University of Helsinki for VarDial 2018
Silfverberg, M., & Drobac, S. (2018) · International Conference on Computational Linguistics · Cited by 3
A 2-Stage Strategy for Non-Stationary Signal Prediction and Recovery Using Iterative Filtering and Neural Network
Zhou, F., Zhou, H., Yang, Z., & Yang, L. (2019) · Journal of Computer Science and Technology · doi:10.1007/s11390-019-1913-0 · Cited by 4
Overview and Choice of Artificial Intelligence Approaches for Night-Time Adaptive Optics Reconstruction
Riesgo, F. G., Gómez, S. L. S., Santos, J., Alonso, E. D., & Lasheras, F. S. (2021) · Mathematics · doi:10.3390/math9111220 · Cited by 3
“In optical applications specifically, some kinds of artificial neural networks as the convolutional ones [8], have shown good results in image recognition, language processing [9], image classification [10], etc.”
Background
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Authors: Goldberg, Y.
Affiliations: Bar-Ilan University (IL)
Corresponding author: Goldberg, Yoav
ORCID: Goldberg, Yoav
Venue: Synthesis Lectures on Human Language Technologies
Publisher: Springer International Publishing
Published: 2017
ISSN: 1947-4040 (ISSN-L)
1947-4059
DOI: 10.1007/978-3-031-02165-7
OpenAlex: W2606089314
Semantic Scholar: 6c27d9844fcb94dfcd6decab7df559134d6d4fd7
Cited by: 821
References: 75
Citations by year: 2026: 38 · 2025: 72 · 2024: 60 · 2023: 101 · 2022: 111 · 2021: 134 · 2020: 142 · 2019: 92 · 2018: 64 · 2017: 6
FWCI: 37.46
Type: book
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
Locations: Synthesis lectures on human language technologies (publishedVersion)
CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
Keywords: artificial neural networks, natural language processing, machine learning models

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