Search Results - Multi-label Text Classification in Machine Learning*

Ontology based Feature Selection and Weighting for Text classification using Machine Learning

Authors: Djelloul Bouchiha Abdelghani Bouziane Noureddine Doumi

Source: Journal of Information Technology and Computing. 4:1-14

Subject Terms: FOS: Computer and information sciences, Artificial intelligence, Support vector machine, Class (philosophy), Feature (linguistics), 02 engineering and technology, Epistemology, Weighting, Pattern recognition (psychology), Feature vector, Web Data Extraction and Crawling Techniques, Machine Learning Algorithms, Selection (genetic algorithm), Artificial Intelligence, Multi-label Text Classification in Machine Learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Syntax, Feature Selection, Multi-label Learning, Content Adaptation, Text Classification, Preprocessor, Ontology, Natural language processing, 4. Education, Linguistics, Computer science, FOS: Philosophy, ethics and religion, Automatic Keyword Extraction from Textual Data, Philosophy, Computer Science, Physical Sciences, Feature selection, FOS: Languages and literature, Medicine, Radiology, Information Systems

Mao-Zedong at SemEval-2023 Task 4: Label Represention Multi-Head Attention Model with Contrastive Learning-Enhanced Nearest Neighbor Mechanism for Multi-Label Text Classification

Authors: Zhang Che Pingan Liu Z. J. Xiao et al.

Source: Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023). :426-432

Subject Terms: FOS: Computer and information sciences, Artificial intelligence, Economics, Sequence-to-Sequence Learning, Semantic Similarity, Quantum mechanics, Task (project management), Head (geology), Artificial Intelligence, Multi-label Text Classification in Machine Learning, Multi-label Learning, Natural Language Processing, Computer Science - Computation and Language, Natural language processing, Physics, Word Representation, Mechanism (biology), Geomorphology, Geology, FOS: Earth and related environmental sciences, Named Entity Recognition, Computer science, Management, Automatic Keyword Extraction from Textual Data, Computer Science, Physical Sciences, k-nearest neighbors algorithm, Computation and Language (cs.CL), SemEval

Access URL: http://arxiv.org/abs/2307.05174

Comparison and analysis of the machine learning in the movie subtitle document classification

Authors: Bill Chu Dongpo Xu Dongze Wu

Source: Applied and Computational Engineering. 5:642-648

Subject Terms: Artificial intelligence, Natural language processing, 4. Education, Video Summarization, Automatic Video Summarization and Analysis, Computer science, Machine Learning Algorithms, Operating system, Sentiment Analysis and Opinion Mining, Artificial Intelligence, Computer Science, Physical Sciences, Multi-label Text Classification in Machine Learning, Machine learning, Information retrieval, Document Categorization, Computer Vision and Pattern Recognition, Multi-label Learning, Feature Selection, Subtitle, Classifier (UML)

Multi-Label Emotion Classification on Code-Mixed Text: Data and Methods

Authors: Iqra Ameer Grigori Sidorov Helena Gómez-Adorno et al.

Source: IEEE Access, Vol 10, Pp 8779-8789 (2022)

Subject Terms: FOS: Computer and information sciences, Artificial intelligence, Text Mining, Economics, Set (abstract data type), 02 engineering and technology, Anger, 01 natural sciences, Detection and Prevention of Phishing Attacks, Sentiment analysis, Task (project management), Artificial Intelligence, Multi-label Text Classification in Machine Learning, Sadness, Machine learning, Roman Urdu and English, 0202 electrical engineering, electronic engineering, information engineering, Psychology, multi-label emotion classification, SMS messages, Multi-label Learning, Code-mixed text, 0105 earth and related environmental sciences, Code (set theory), Psychiatry, Geography, Natural language processing, classical machine learning, deep learning, Linguistics, Computer science, Urdu, TK1-9971, FOS: Philosophy, ethics and religion, Management, Programming language, FOS: Psychology, Philosophy, Sentiment Analysis and Opinion Mining, Emotion Recognition, Computer Science, Physical Sciences, Emotion classification, FOS: Languages and literature, Electrical engineering. Electronics. Nuclear engineering, Benchmark (surveying), Geodesy, Information Systems

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/9668973/09682721.pdf
https://doaj.org/article/e9730bad0722445fbf5b56efd1b29878

A HYBRID FEATURE SELECTION APPROACH FOR ROMAN URDU TEXT CLASSIFICATION

Authors: Waqas Azeem Aziza Chakir

Source: Journal of Advancement in Computing. 2:39-44

Subject Terms: Artificial intelligence, Feature (linguistics), Natural language processing, 4. Education, Linguistics, Pattern recognition (psychology), 16. Peace & justice, Urdu, Computer science, FOS: Philosophy, ethics and religion, Philosophy, Selection (genetic algorithm), Artificial Intelligence, Multi-label Text Classification in Machine Learning, Computer Science, Physical Sciences, Feature selection, FOS: Languages and literature, Feature Selection, Text Classification

An Efficient Approach for Code-Mixed Emotion Classification Applying Machine Learning

Authors: Ahmad Mahmood Miguel Torres-Ruiz Zainab Ahmad et al.

Source: IEEE Access, Vol 13, Pp 166973-166986 (2025)

Subject Terms: Code-mixed text, English and Roman Urdu, emotion classification, multi-label emotion classification, classical machine learning, generative AI, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Relation: https://ieeexplore.ieee.org/document/11124195/; https://doaj.org/toc/2169-3536; https://doaj.org/article/305f717d163a4891a6e67fec2dace93e

Availability: https://doi.org/10.1109/ACCESS.2025.3598754
https://doaj.org/article/305f717d163a4891a6e67fec2dace93e

An Interpretable Fuzzy Graph Learning for Label Propagation Assisting Data Classification

Authors: Cherukula Madhu M. Sudhakar

Source: IEEE Transactions on Fuzzy Systems. 32:1331-1345

Subject Terms: Intuitionistic Fuzzy Sets, Artificial intelligence, Coordinate descent, Social Sciences, Multi-Criteria Decision Making, Management Science and Operations Research, Pattern recognition (psychology), Computer science, Feature vector, Graph, Decision Sciences, Urban Studies, Theoretical computer science, Fuzzy Sets, Artificial Intelligence, Outlier, Multi-label Text Classification in Machine Learning, Computer Science, Physical Sciences, Feature selection, Machine learning, Interpretability, Dynamics of Urban Structure through Spatial Network Analysis, Multi-label Learning, Data mining

A Hybrid Deep Learning GRU based Approach for Text Classification using Word Embedding

Authors: Poluru Eswaraiah Hussain Syed

Source: EAI Endorsed Transactions on Internet of Things. 10

Subject Terms: Artificial neural network, Artificial intelligence, Word (group theory), Recurrent neural network, Word embedding, Set (abstract data type), 02 engineering and technology, 03 medical and health sciences, Context (archaeology), 0302 clinical medicine, Artificial Intelligence, Multi-label Text Classification in Machine Learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Multi-label Learning, Text Classification, Biology, Natural Language Processing, Topic Modeling, Natural language processing, Word Representation, Paleontology, Deep learning, Semantics (computer science), Linguistics, Named Entity Recognition, Computer science, FOS: Philosophy, ethics and religion, Programming language, Automatic Keyword Extraction from Textual Data, Philosophy, Categorization, Computer Science, Physical Sciences, FOS: Languages and literature, Embedding

Aspect Based Sentiment Analysis: Feature Extraction using Latent Dirichlet Allocation (LDA) and Term Frequency - Inverse Document Frequency (TF-IDF) in Machine Learning (ML)

Authors: Shakirah Mohd Sofi Ali Selamat

Source: Malaysian Journal of Information and Communication Technology (MyJICT). :169-179

Subject Terms: Artificial intelligence, Text Mining, Feature (linguistics), Latent Dirichlet allocation, Geometry, Pattern recognition (psychology), Twitter Sentiment, Quantum mechanics, Term (time), tf–idf, Topic model, Artificial Intelligence, Aspect-based Sentiment Analysis, Multi-label Text Classification in Machine Learning, Sentiment Analysis, FOS: Mathematics, Natural language processing, Physics, Linguistics, Computer science, FOS: Philosophy, ethics and religion, 3. Good health, Automatic Keyword Extraction from Textual Data, Philosophy, Sentiment Analysis and Opinion Mining, Computer Science, Physical Sciences, FOS: Languages and literature, Feature extraction, Inverse, Mathematics

Beyond Text: Incorporating Metadata and Label Structure for Multi-Label Document Classification using Heterogeneous Graphs

Authors: Chenchen Ye Linhai Zhang Yulan He et al.

Source: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. :3162-3171

Subject Terms: Artificial intelligence, Economics, Multi-label classification, Set (abstract data type), 02 engineering and technology, Handwriting Recognition and Text Detection, Graph, Theoretical computer science, Artificial Intelligence, Hierarchy, Market economy, Multi-label Text Classification in Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Information retrieval, Multi-label Learning, Data mining, Natural Language Processing, Metadata, Text Detection, Document Image Analysis, Computer science, Programming language, World Wide Web, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition

Access URL: https://aclanthology.org/2021.emnlp-main.253.pdf

Word Sense Disambiguation Based Sentiment Classification Using Linear Kernel Learning Scheme

Authors: P. Ramya B. Karthik

Source: Intelligent Automation & Soft Computing. 36:2379-2391

Subject Terms: FOS: Computer and information sciences, Artificial intelligence, Support vector machine, Text Mining, Economics, Feature (linguistics), Word (group theory), Automatic summarization, Web Data Extraction and Crawling Techniques, Document classification, Sentiment analysis, Task (project management), Context (archaeology), Artificial Intelligence, Multi-label Text Classification in Machine Learning, Machine learning, Information retrieval, Multi-label Learning, Text Classification, Biology, Natural language processing, 4. Education, Paleontology, Linguistics, Bag-of-words model, Computer science, FOS: Philosophy, ethics and religion, Management, Philosophy, Sentiment Analysis and Opinion Mining, Emotion Recognition, Computer Science, Physical Sciences, FOS: Languages and literature, Document Categorization, Polysemy, Information Systems, SemEval

A high-quality feature selection method based on frequent and correlated items for text classification

Authors: Heba Mamdouh Farghaly Tarek Abd El‐Hafeez

Source: Soft Computing. 27:11259-11274

Subject Terms: FOS: Computer and information sciences, Artificial intelligence, Metric (unit), Feature (linguistics), FOS: Political science, Handling Imbalanced Data in Classification Problems, FOS: Law, 02 engineering and technology, Epistemology, Pattern recognition (psychology), Detection and Prevention of Phishing Attacks, Selection (genetic algorithm), Engineering, Artificial Intelligence, Multi-label Text Classification in Machine Learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Feature Selection, Multi-label Learning, Text Classification, Data mining, Political science, Cost-Sensitive Learning, Linguistics, Computer science, Process (computing), FOS: Philosophy, ethics and religion, Philosophy, Operating system, Spam Detection, Operations management, Computer Science, Physical Sciences, Feature selection, Quality (philosophy), FOS: Languages and literature, Relevance (law), Law, Information Systems

BdRegionText: resource creation and evaluation for Bangla regional text classification with machine learning.

Authors: Sultana, Babe Hoque, S. M. Mirajul Hussain, Md Gulzar et al.

Source: Indonesian Journal of Electrical Engineering & Computer Science; Oct2025, Vol. 40 Issue 1, p411-425, 15p

Subject Terms: MACHINE learning, NATURAL language processing, SOCIOCULTURAL factors, FEATURE extraction, DIALECTS, STATISTICAL accuracy, BENGALI language

Geographic Terms: BANGLADESH, CHITTAGONG (Bangladesh)

A Hybrid Principal Label Space Transformation-Based Binary Relevance Support Vector Machine and Q-Learning Algorithm for Multi-label Classification.

Authors: Ebrahimi, Seyed Hossein Seyed¹ (AUTHOR) hossein.seyedebrahimi@iau.ac.ir

Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ). Jan2025, Vol. 50 Issue 2, p851-875. 25p.

Subject Terms: *SUPPORT vector machines, *ARTIFICIAL intelligence, *IMAGE processing, *CLASSIFICATION algorithms, *MACHINE learning

Multi-label classification via closed frequent labelsets and label taxonomies

Authors: Mauri Ferrandin Ricardo Cerri

Source: Soft Computing. 27:8627-8660

Subject Terms: Artificial intelligence, Support vector machine, Economics, Text Compression and Indexing Algorithms, Multi-label classification, 15. Life on land, Pattern recognition (psychology), Computer science, Directed acyclic graph, Algorithm, Multiclass classification, Artificial Intelligence, Hierarchy, Market economy, Multi-label Text Classification in Machine Learning, Computer Science, Physical Sciences, Shape Matching and Object Recognition, Machine learning, Computer Vision and Pattern Recognition, Multi-label Learning, Classifier (UML), Data mining

Cluster-based ensemble learning model for improving sentiment classification of Arabic documents

Authors: Rana Husni Al Mahmoud Bassam Hammo Hossam Faris

Source: Natural Language Engineering. 30:1091-1129

Subject Terms: Artificial intelligence, Class (philosophy), Support vector machine, Handling Imbalanced Data in Classification Problems, 02 engineering and technology, Cluster analysis, Artificial Intelligence, Aspect-based Sentiment Analysis, Ensemble learning, Multi-label Text Classification in Machine Learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Multi-label Learning, Ensemble Methods, 10. No inequality, Data mining, Cost-Sensitive Learning, Naive Bayes classifier, Imbalanced Data, 4. Education, Undersampling, Computer science, Sentiment Analysis and Opinion Mining, Computer Science, Physical Sciences, Random forest

Battle Royale Optimization with Fuzzy Deep Learning for Arabic Sentiment Classification

Authors: Manar Ahmed Hamza Hala J. Alshahrani Jaber S. Alzahrani et al.

Source: Computer Systems Science and Engineering. 46:2619-2635

Subject Terms: Artificial intelligence, Text Mining, Natural language processing, 4. Education, Botany, Discriminative model, 02 engineering and technology, Computer science, Automatic Keyword Extraction from Textual Data, Sentiment analysis, Identification (biology), Sentiment Analysis and Opinion Mining, Artificial Intelligence, Categorization, Aspect-based Sentiment Analysis, Emotion Recognition, Computer Science, Physical Sciences, Multi-label Text Classification in Machine Learning, Machine learning, Sentiment Analysis, 0202 electrical engineering, electronic engineering, information engineering, Biology

Machine Learning and Feature Selection Approaches for Categorizing Arabic Text: Analysis, Comparison, and Proposal

Authors: Ayat Elnahas Nawal El‐Fishawy Mohamed Abdalla Nour et al.

Source: The Egyptian Journal of Language Engineering. 7:1-19

Subject Terms: Artificial intelligence, Arabic, Natural language processing, Feature (linguistics), 4. Education, Linguistics, 02 engineering and technology, Computer science, FOS: Philosophy, ethics and religion, Machine Learning Algorithms, Philosophy, Selection (genetic algorithm), Artificial Intelligence, Multi-label Text Classification in Machine Learning, Computer Science, Physical Sciences, Feature selection, Machine learning, FOS: Languages and literature, 0202 electrical engineering, electronic engineering, information engineering, Document Categorization, Feature Selection, Multi-label Learning, Text Classification

Access URL: https://ejle.journals.ekb.eg/article_112830_87e2e565441360492b7b5d622bcb24e5.pdf
https://journals.ekb.eg/article_112830.html
https://ejle.journals.ekb.eg/article_112830_87e2e565441360492b7b5d622bcb24e5.pdf
https://ejle.journals.ekb.eg/article_112830.html

Classification of Poetry Text Into the Emotional States Using Deep Learning Technique

Authors: Shakeel Ahmad Muhammad Zubair Asghar Fahad Alotaibi et al.

Source: IEEE Access, Vol 8, Pp 73865-73878 (2020)

Subject Terms: Artificial intelligence, emotional states, 02 engineering and technology, Anger, poetry text, attention-based C-BiLSTM, Artificial Intelligence, emotion recognition, Multi-label Text Classification in Machine Learning, Sadness, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Psychology, formal text, Psychiatry, Natural language processing, Deep learning, Computer science, TK1-9971, Automatic Keyword Extraction from Textual Data, FOS: Psychology, Sentiment Analysis and Opinion Mining, Literature, Emotion Recognition, Computer Science, Physical Sciences, Poetry, Electrical engineering. Electronics. Nuclear engineering, Art

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09066983.pdf
https://doaj.org/article/3a6ccdd7dcab4e0cad1fdd66fa8419b3
https://dblp.uni-trier.de/db/journals/access/access8.html#AhmadAAK20
https://ieeexplore.ieee.org/document/9066983
https://doi.org/10.1109/ACCESS.2020.2987842
http://ieeexplore.ieee.org/document/9066983

Optimal feature selection using novel flamingo search algorithm for classification of COVID-19 patients from clinical text

Authors: Mahdi, Amir Yasseen Yuhaniz, Siti Sophiayati

Source: Mathematical Biosciences and Engineering, Vol 20, Iss 3, Pp 5268-5297 (2023)

Subject Terms: Radiology, Nuclear Medicine and Imaging, Artificial intelligence, Support Vector Machine, Feature (linguistics), Health Professions, Infectious disease (medical specialty), 02 engineering and technology, Pattern recognition (psychology), feature selection, COVID-19 Testing, Selection (genetic algorithm), Health Information Management, Multi-label Text Classification in Machine Learning, Pathology, 0202 electrical engineering, electronic engineering, information engineering, Disease, Feature Selection, Applications of Deep Learning in Medical Imaging, 3. Good health, FOS: Philosophy, ethics and religion, Algorithm, covid-19, Physical Sciences, Feature selection, Medicine, Algorithms, Biotechnology, QA75 Electronic computers. Computer science, Birds, Artificial Intelligence, Virology, Health Sciences, QA1-939, Animals, Humans, natural language processing, Machine Learning in Healthcare and Medicine, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), COVID-19, Outbreak, Linguistics, Computer science, Coronavirus disease 2019 (COVID-19), Philosophy, Computer Science, FOS: Languages and literature, clinical text classification, 2019-20 coronavirus outbreak, TP248.13-248.65, Mathematics, binary flamingo search algorithm

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/36896545
https://doaj.org/article/9e2917b519b04cb197917516135b409b