Information extraction from green channel textual records on expressways using hybrid deep learning by Jiaona Chen, Jing Zhang, Weijun Tao, Yinli Jin, Heng Fan

“…Eight entities are designed and proposed in the NER processing for the expressway green channel. three typical pre-trained natural language processing models are utilized and compared to recognize entities and obtain feature vectors, including bidirectional encoder representations from transformer (BERT), ALBERT, and RoBERTa. …”
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Keywords, morpheme parsing and syntactic trees: features for text complexity assessment by Dmitry A. Morozov, Ivan A. Smal, Timur A. Garipov, Anna V. Glazkova

“…With the development of natural language processing algorithms, the space of used features is expanding. …”
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Investigating on Creating a Software Application for an On-Screen Explanatory Dictionary by Валентина Плескач, Романас Тумасоніс, Назар Єсипчук, Олег Калмиков, Аліна Акімова

“…The research employs an analysis of modern technologies for developing on-screen explanatory dictionaries, including the use of natural language processing (NLP) platforms, artificial intelligence (AI), machine learning, and adaptive user interface technologies. …”
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Exploring Information Interaction Preferences in an LLM-Assisted Learning Environment with a Topic Modeling Framework by Yiming Taclis Luo, Ting Liu, Patrick Cheong-Iao Pang, Zhuo Wang, Ka Ian Chan

“…This study provides a new approach to studying the interaction between students and LLM in engineering education by using natural language processing to process prompts, contributing to the exploration of the performance of students with different performance levels in professional academic writing using LLM.…”
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Predicting adverse drug reactions in oncology: A critical review of machine learning approaches and future directions by Abid Yahya, Phatsimo Lobelo, Afiya Eram, Sana Althaf Hussain, Irfan Anjum Badruddin, Lory Liza D. Bulay-og, Dionel O. Albina

“…We go over a variety of methods for utilizing both structured and unstructured clinical data, such as supervised, unsupervised, and deep learning models in addition to natural language processing (NLP) strategies. Strong performance has been demonstrated by ensemble techniques like Random Forest and Gradient Boosting, while deep neural networks allow for sophisticated feature extraction, albeit with interpretability issues. …”
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Implementasi Chatbot pada Telegram sebagai Monitoring Assistant dengan Analisis Teks Klasifikasi Menggunakan Metode Support Vector Machine by Dwi Lestari, Lukman Subekti

“…Tujuan dari penelitian ini adalah membuat klasifikasi intent pada chatbot dengan menggunakan teknologi Natural Language Processing dan algoritma Support Vector Machine (SVM). …”
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Tendencias en la investigación para el control del discurso de odio en las redes sociales para el período 2016-2022 by Ana M. Sánchez-Sánchez, David Ruiz-Muñoz, Francisca J. Sánchez-Sánchez

“…El deep learning y el natural language processing systems fueron identificados como los mecanismos de control más empleados. …”
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MLAL: Multiple Prompt Learning and Generation of Auxiliary Labeled Utterances for Emotion Recognition in Conversations by Zhinan Gou, Yuxin Chen, Yuchen Long, Mengyao Jia, Zhili Liu, Jun Zhu

“…Emotion Recognition in Conversations (ERC) is one of the most prominent research directions in the field of Natural Language Processing (NLP). It aims to accurately identify the emotional state expressed in conversations and is widely applied in psychology, education, and healthcare. …”
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The impact of cultural factors on digital marketing strategies with Machine learning and honey bee Algorithm (HBA) by Muhammad Khan, Masood Ahmad, Rakhmonov Dilshodjon Alidjonovich, Kalonov Mukhiddin Bakhritdinovich, Kurbanbekova Mohichehra Turobjonovna, Imomov Jamshidxon Odilovich

“…Experimental results demonstrate that machine learning models effectively capture cultural preferences, and HBA significantly enhances marketing effectiveness, leading to a 20% increase in engagement and a 15% improvement in click-through rates (CTR). Natural Language Processing (NLP) methods are used to gain cultural insights from consumer data, while clustering algorithms segment the market based on these factors. …”
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Towards an Estonian dataset on document-level subjectivity by Karl Gustav Gailit, Kadri Muischnek, Kairit Sirts

“…Subjectivity has been explored within many fields of linguistics, including pragmatics and formal semantics, as well as natural ­ language processing where computational methods are used to create models for detecting subjectivity, often for further processing. …”
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Image Captioning Based on Semantic Scenes by Fengzhi Zhao, Zhezhou Yu, Tao Wang, Yi Lv

“…With the development of artificial intelligence and deep learning technologies, image captioning has become an important research direction at the intersection of computer vision and natural language processing. The purpose of image captioning is to generate corresponding natural language descriptions by understanding the content of images. …”
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Prediction of depression in individuals at high familial risk of mood disorders using functional magnetic resonance imaging. by Heather C Whalley, Jessika E Sussmann, Liana Romaniuk, Tiffany Stewart, Martina Papmeyer, Emma Sprooten, Suzanna Hackett, Jeremy Hall, Stephen M Lawrie, Andrew M McIntosh

“…<h4>Methods</h4>We studied 98 young unaffected individuals at high familial risk of BD and 58 healthy controls using functional Magnetic Resonance Imaging (fMRI) scans and a task involving executive and language processing. Twenty of the high-risk subjects subsequently developed MDD after the baseline fMRI scan.…”
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Cross-lingual hate speech detection using domain-specific word embeddings. by Ayme Arango Monnar, Jorge Perez Rojas, Barbara Polete Labra

“…Most supervised learning resources for this task, such as labeled datasets and Natural Language Processing (NLP) tools, have been specifically tailored for English. …”
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Semantic and ontology-based analysis of regulatory documents for construction industry digitalization by Zarina Kabzhan, Alexandr Shakhnovich, Sergey Gorshkov, Yussuf Yemenov, Fedor Gorshkov, Nazym Shogelova

“…The aim of this study is to develop a method for the automated analysis of regulatory documents in the construction sector based on the integration of ontological modeling and natural language processing (NLP) techniques. The relevance of the topic is driven by the need for the digital transformation of construction standardization, which involves eliminating redundant provisions, logical inconsistencies, and outdated references in the regulatory framework. …”
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Text2SQL Business Intelligence System Based on Retrieval‐Augmented Generation (RAG) by Jie Liu, Shiwei Chu

“…Advances in natural language processing, particularly deep learning generative models, have enabled text‐to‐SQL (text2SQL) conversion, making database interaction more intuitive. …”
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The influence of text segmentation on garden path processing: evidence from self-paced reading and eye-tracking by Andromachi Tsoukala, Margreet Vogelzang, Ianthi Maria Tsimpli

“…Despite this prevalence, their effects on parsing and interpretation have been markedly understudied in previous research on written language processing. To shed light on these effects, we conducted a self-paced reading and an eye-tracking study in which participants read multiline texts that contained direct object–subject ambiguity, a type of temporary clause boundary ambiguity. …”
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Text classification to streamline online wildlife trade analyses. by Oliver C Stringham, Stephanie Moncayo, Katherine G W Hill, Adam Toomes, Lewis Mitchell, Joshua V Ross, Phillip Cassey

“…Other scientific disciplines have solved similar problems using machine learning and natural language processing models, such as text classifiers. Here, we test the ability of a suite of text classifiers to extract relevant advertisements from wildlife trade occurring on the Internet. …”
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Library Chat Transcript Evaluation for User Sentiment During the COVID-19 Pandemic by Kathryn Barrett, Ansh Sharma

“…Methods – The researchers analyzed 3,339 chat transcripts using VADER, a free, open-source Python natural language processing library for sentiment analysis. We tested the significance of relationships between study variables and sentiment score using either a two-samples t-test or ANOVA. …”
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A Python Framework for Crop Yield Estimation Using Sentinel-2 Satellite Data by Konstantinos Ntouros, Konstantinos Papatheodorou, Georgios Gkologkinas, Vasileios Drimzakas-Papadopoulos

“…Expanding the dataset across diverse regions and incorporating machine learning and Natural Language Processing (NLP) could enhance automation, usability, and predictive accuracy.…”
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Comparison of Feature Extraction in Support Vector Machine (SVM) Based Sentiment Analysis System by Imam Fahrur Rozi, Irma Maulidia, Mamluatul Hani’ah, Rakhmat Arianto, Dika Rizky Yunianto, Ahmadi Yuli Ananta

“… Sentiment analysis plays a crucial role in natural language processing by identifying and categorizing opinions or emotions conveyed in textual data. …”
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