Výsledky vyhledávání - Automatic Keyword Extraction from Textual Data

A survey on narrative extraction from textual data

Autoři: Brenda Salenave Santana Ricardo Campos Evelin Amorim a další

Zdroj: Artificial Intelligence Review. 56:8393-8435

Témata: Neural Machine Translation, Artificial intelligence, Economics, FOS: Political science, Extraction, Computational linguistics, FOS: Law, 02 engineering and technology, Mathematical analysis, Data science, Task (project management), Identification (biology), Narrative, Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, 10. No inequality, Political science, Biology, Natural Language Processing, Visualization, Narrative inquiry, Domain (mathematical analysis), Natural language processing, Word Representation, Politics, Botany, Linguistics, Statistical Machine Translation and Natural Language Processing, 16. Peace & justice, Computer science, Language Modeling, Process (computing), FOS: Philosophy, ethics and religion, Management, 3. Good health, Automatic Keyword Extraction from Textual Data, Narrative criticism, Philosophy, Operating system, Computer Science, Physical Sciences, Narrative network, FOS: Languages and literature, Textual Data, Representation (politics), Law, Mathematics

An unsupervised linguistic-based model for automatic glossary term extraction from a single PDF textbook

Autoři: Ashraf Soliman

Zdroj: Education and Information Technologies. 28:16089-16125

Témata: FOS: Computer and information sciences, Artificial intelligence, Sentence, Extraction, 02 engineering and technology, Quantum mechanics, Mathematical analysis, Information Retrieval Techniques and Evaluation, Term (time), Artificial Intelligence, Computer security, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Key (lock), Text Classification, Language Models, Natural Language Processing, Domain (mathematical analysis), Topic Modeling, Natural language processing, Physics, 4. Education, Word Representation, Linguistics, Computer science, Language model, FOS: Philosophy, ethics and religion, Automatic Keyword Extraction from Textual Data, Philosophy, Natural language, Computer Science, Physical Sciences, FOS: Languages and literature, Chunking (psychology), Lexical analysis, Glossary, Mathematics, Information Systems

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

Autoři: Shakirah Mohd Sofi Ali Selamat

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

Témata: 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

Student textual feedback sentiment analysis using machine learning techniques to improve the quality of education

Autoři: Naseer Ahmed Mansoor Ahmed Khouro Afrasiyab Khan a další

Zdroj: Pakistan Journal of Engineering, Technology & Science. 11:32-40

Témata: Artificial intelligence, Epistemology, Data science, Sentiment analysis, Artificial Intelligence, Machine learning, Psychology, 10. No inequality, Student Engagement, Educational Data Mining, Data-driven Education, Natural language processing, 4. Education, Computer science, Learning Analytics, Mathematics education, Computer Science Applications, FOS: Philosophy, ethics and religion, 3. Good health, Automatic Keyword Extraction from Textual Data, FOS: Psychology, Philosophy, Sentiment Analysis and Opinion Mining, Computer Science, Physical Sciences, Quality (philosophy), Student Performance Prediction, Educational Data Mining and Learning Analytics

Development of an annotated Yoruba text corpus for automatic event extraction

Autoři: Adebisi Joseph Ademusire Olufemi D. Ninan

Témata: Artificial intelligence, Domain (mathematical analysis), Annotation, Natural language processing, Physics, 4. Education, Yoruba, Linguistics, Statistical Machine Translation and Natural Language Processing, 15. Life on land, Computer science, Mathematical analysis, Quantum mechanics, FOS: Philosophy, ethics and religion, Automatic Keyword Extraction from Textual Data, Philosophy, Artificial Intelligence, Computer Science, Physical Sciences, FOS: Languages and literature, FOS: Mathematics, Textual Data, Event (particle physics), Mathematics, Natural Language Processing

Improving Performance of Automatic Keyword Extraction (AKE) Methods Using PoS Tagging and Enhanced Semantic-Awareness

Autoři: Altuncu, Enes Nurse, Jason R. C. Xu, Yang a další

Témata: QA Mathematics (inc Computing science), QA 76 Software, computer programming, QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems), TK7882.P3 Pattern recognition systems, TK7885 Computer engineering. Computer hardware, Article, PeerReviewed

URL: https://kar.kent.ac.uk/110621/
https://doi.org/10.3390/info16070601
https://kar.kent.ac.uk/110621
https://doi.org/10.3390/info16070601
10.3390/info16070601

More than Classification: A Unified Framework for Event Temporal Relation Extraction

Autoři: Qiaoli Huang Yutong Hu Shengqi Zhu a další

Zdroj: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). :9631-9646

Témata: FOS: Computer and information sciences, Relationship extraction, Relation (database), Artificial intelligence, Economics, Extraction, Leverage (statistics), Quantum mechanics, Complex event processing, Task (project management), Theoretical computer science, Artificial Intelligence, Multi-label Text Classification in Machine Learning, Multi-label Learning, Event (particle physics), Data mining, Natural Language Processing, Computer Science - Computation and Language, Topic Modeling, Physics, Named Entity Recognition, Computer science, Programming language, Management, Process (computing), Automatic Keyword Extraction from Textual Data, Computer Science, Physical Sciences, Computation and Language (cs.CL)

Přístupová URL adresa: http://arxiv.org/abs/2305.17607

Comparative analysis of TF-IDF and loglikelihood method for keywords extraction of twitter data

Autoři: Muhammad Adeel Abid Muhammad Faheem Mushtaq Urooj Akram a další

Zdroj: Mehran University Research Journal of Engineering and Technology, Vol 42, Iss 1, Pp 88-94 (2023)

Témata: Technology, Science, FOS: Political science, FOS: Law, 02 engineering and technology, Quantum mechanics, 7. Clean energy, Term (time), tf–idf, Data science, Social media, Artificial Intelligence, Computer security, Field (mathematics), Multi-label Text Classification in Machine Learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Information retrieval, Key (lock), 10. No inequality, Political science, Physics, 4. Education, Pure mathematics, Engineering (General). Civil engineering (General), Computer science, Automatic Keyword Extraction from Textual Data, World Wide Web, Computer Science, Physical Sciences, Relevance (law), TA1-2040, Textual Data, Law, Mathematics

Přístupová URL adresa: https://doaj.org/article/4b30b6e422084ad68d07d5dc38d1d35e

Automatic Generation of Restaurant Reviews Using Natural Language Processing

Autoři: Idalia Maldonado Castillo Ileana Miranda Alexis Olvera Mendoza

Zdroj: Springer Proceedings in Business and Economics ISBN: 9783031510373

Témata: Artificial intelligence, Sociology and Political Science, Knowledge management, FOS: Political science, Social Sciences, Set (abstract data type), FOS: Law, 7. Clean energy, Tourism, Data science, 12. Responsible consumption, FOS: Economics and business, Sentiment analysis, Artificial Intelligence, Promotion (chess), 11. Sustainability, User-Generated Content, Business, Political science, Marketing, 2. Zero hunger, Geography, Impact of Social Media on Consumer Behavior, Politics, Computer science, Programming language, Automatic Keyword Extraction from Textual Data, Sentiment Analysis and Opinion Mining, Archaeology, Computer Science, Physical Sciences, 8. Economic growth, Law

A Multimodal Latent-Features-Based Service Recommendation System for the Social Internet of Things

Autoři: Amar Khelloufi Huansheng Ning Abdenacer Naouri a další

Zdroj: IEEE Transactions on Computational Social Systems. 11:5388-5403

Témata: Big Data Analysis in Various Industries, FOS: Computer and information sciences, Internet of Things, Ontology-Based Healthcare Context Information Modeling, Health Professions, Computer Science - Information Retrieval, FOS: Economics and business, Health Information Management, Artificial Intelligence, Computer security, Context Information Model, Service (business), Health Sciences, Business, P2P Cloud Network Services, Social and Information Networks (cs.SI), Graph-Based, Marketing, Topic Modeling, Computer Science - Social and Information Networks, Computer science, Automatic Keyword Extraction from Textual Data, World Wide Web, Computer Science, Physical Sciences, Internet privacy, Bio-detection for Smart Health Service, Information Retrieval (cs.IR), The Internet, Information Systems

Přístupová URL adresa: http://arxiv.org/abs/2306.01163

Subject Detection of Algerian Posts for Opinion Analysis

Autoři: Kheira Zineb Bousmaha Khaoula Hamadouche Nawel Cheurfaoui a další

Zdroj: Ingénierie des systèmes d information. 29:821-829

Témata: FOS: Computer and information sciences, Text Mining, FOS: Political science, 4. Education, 16. Peace & justice, Computer science, Detection and Prevention of Phishing Attacks, Automatic Keyword Extraction from Textual Data, World Wide Web, Sentiment Analysis and Opinion Mining, Behavioral Analysis, 5. Gender equality, Artificial Intelligence, Aspect-based Sentiment Analysis, Subject (documents), Computer Science, Physical Sciences, Bot Detection, 8. Economic growth, Sentiment Analysis, Information retrieval, 10. No inequality, Political science, Information Systems

Approaches, tools, algorithms, and methods for automatic term extraction: A systematic literature mapping

Autoři: Juan Carlos Blandón Andrade Carlos Mario Medina Otálvaro Carlos Mario Zapata Jaramillo a další

Témata: Neural Machine Translation, Artificial intelligence, Extraction, Mathematical analysis, Quantum mechanics, Term (time), Lexical Database, Machine Translation, Artificial Intelligence, FOS: Mathematics, Information retrieval, Biology, Natural Language Processing, Scientific literature, Domain (mathematical analysis), Natural language processing, Physics, Paleontology, Linguistics, Statistical Machine Translation and Natural Language Processing, Terminology, Computer science, FOS: Philosophy, ethics and religion, Automatic Keyword Extraction from Textual Data, Lexicographical order, Philosophy, Combinatorics, Computer Science, Physical Sciences, FOS: Languages and literature, Mathematics

Emo-SL Framework: Emoji Sentiment Lexicon Using Text-Based Features and Machine Learning for Sentiment Analysis

Autoři: Manar Alfreihat Omar Almousa Yahya Tashtoush a další

Zdroj: IEEE Access, Vol 12, Pp 81793-81812 (2024)

Témata: Artificial intelligence, Emoji sentiment lexicon for Arabic (Emo-SL), machine learning (ML), Natural language processing, data modeling and analysis, Computer science, TK1-9971, Automatic Keyword Extraction from Textual Data, Emoji, Social media, World Wide Web, Sentiment analysis, Sentiment Analysis and Opinion Mining, Artificial Intelligence, Computer Science, Physical Sciences, Machine learning, VADER model, Electrical engineering. Electronics. Nuclear engineering, social media analysis, Lexicon, Arabic-language tweets, Natural Language Processing

Přístupová URL adresa: https://doaj.org/article/784f5fc567c749a98a58589d923d3c16

TED Talks Comments Sentiment Classification Using Machine Learning Algorithms

Autoři: Mohamed Elbadaoui Noreddine Gherabi Fatima Quanouni

Zdroj: Revue d'Intelligence Artificielle. 38:885-892

Témata: Artificial intelligence, Twitter Sentiment, Computer science, 7. Clean energy, Automatic Keyword Extraction from Textual Data, Machine Learning, Algorithm, Sentiment analysis, Sentiment Analysis and Opinion Mining, Artificial Intelligence, Emotion Recognition, Aspect-based Sentiment Analysis, Computer Science, Physical Sciences, Machine learning, Sentiment Analysis

Semantic information extraction and search of mineral exploration data using text mining and deep learning methods

Autoři: Qinjun Qiu Miao Tian Liufeng Tao a další

Zdroj: Ore Geology Reviews. 165:105863

Témata: Table (database), Information extraction, Text Mining, Biomedical Ontologies and Text Mining, Latent Dirichlet allocation, Extraction, Data science, 12. Responsible consumption, Knowledge extraction, Topic model, Artificial Intelligence, Biochemistry, Genetics and Molecular Biology, 11. Sustainability, Information retrieval, 14. Life underwater, Molecular Biology, Mineral exploration, Data mining, Natural Language Processing, Visualization, Mineral resource classification, Life Sciences, Geology, FOS: Earth and related environmental sciences, 15. Life on land, Computer science, Automatic Keyword Extraction from Textual Data, Geophysics, Geochemistry, 13. Climate action, Computer Science, Physical Sciences, Information Retrieval, 8. Economic growth, Textual Data

Bringing Shape to Textual Data – A Feasible Demonstration

Autoři: Anoud Shaikh Naeem Ahmed Mahoto Mukhtiar Ali Unar

Zdroj: Mehran University Research Journal of Engineering and Technology, Vol 38, Iss 4, Pp 901-914 (2019)

Témata: Parallel computing, Technology, Interface (matter), Artificial intelligence, Science, Epistemology, 02 engineering and technology, Data science, Big data, Knowledge extraction, Artificial Intelligence, Field (mathematics), FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Information retrieval, Unstructured data, Data mining, Knowledge graph, Bubble, Pure mathematics, Engineering (General). Civil engineering (General), 16. Peace & justice, Computer science, FOS: Philosophy, ethics and religion, Automatic Keyword Extraction from Textual Data, World Wide Web, Philosophy, Computer Science, Physical Sciences, Quality (philosophy), TA1-2040, Textual Data, Maximum bubble pressure method, The Internet, Mathematics

Přístupová URL adresa: https://publications.muet.edu.pk/index.php/muetrj/article/download/1237/366
https://doaj.org/article/a45e147ec9924451aca7cfeb7fd89799
https://ui.adsabs.harvard.edu/abs/2019MURJE..38..901S/abstract

Extracting Explicit and Implicit Aspects Using Deep Learning

Autoři: Mikail Muhammad Azman Busst Kalaiarasi Sonai Muthu Anbananthen Subarmaniam Kannan a další

Zdroj: Emerging Science Journal, Vol 8, Iss 1, Pp 61-76 (2024)

Témata: Artificial intelligence, Economics, Social Sciences, explicit aspects, Data science, Sentiment analysis, Task (project management), Artificial Intelligence, Part-of-Speech Tagging, Machine learning, deep learning, aspect extraction, T1-995, Information retrieval, Technology (General), H1-99, Natural language processing, 4. Education, implicit aspects, General Social Sciences, Computer science, Q300-390 Cybernetics, Management, Social sciences (General), Automatic Keyword Extraction from Textual Data, Sentiment Analysis and Opinion Mining, Computational Text Analysis in Social Sciences, Computer Science, Physical Sciences, SemEval

Popis souboru: text

Přístupová URL adresa: https://doaj.org/article/e0ef7309f0b641fabad844f3042968d1

Automatic Information Extraction: A Distant Reading of the Brazilian Historical-Biographical Dictionary

Autoři: Suemi Higuchi Cláudia Freitas Diana Santos a další

Přispěvatelé: Suemi Higuchi Cláudia Freitas Diana Santos a další

Zdroj: Lecture Notes in Computer Science ISBN: 9783030983048

Témata: Artificial intelligence, Information extraction, Annotation, FOS: Political science, Extraction, FOS: Law, Mathematical analysis, Reading (process), Artificial Intelligence, FOS: Mathematics, Political science, Natural Language Processing, Domain (mathematical analysis), Natural language processing, 4. Education, Politics, Linguistics, Statistical Machine Translation and Natural Language Processing, Computer science, FOS: Philosophy, ethics and religion, Automatic Keyword Extraction from Textual Data, Philosophy, Computer Science, Physical Sciences, FOS: Languages and literature, Object (grammar), Law, Mathematics

Popis souboru: application/pdf

Přístupová URL adresa: http://hdl.handle.net/10852/98061
https://doi.org/10.1007/978-3-030-98305-5_14
https://hdl.handle.net/10400.26/43619

Automated Abstractive Text Summarization Using Multidimensional Long Short-Term Memory

Autoři: Anwar Khan

Zdroj: Quaid-e-Awam University Research Journal of Engineering, Science & Technology. 21:01-11

Témata: Data Quality Assessment and Improvement, Artificial intelligence, Topic Modeling, Natural language processing, Physics, Social Sciences, Automatic summarization, Management Science and Operations Research, Computer science, Quantum mechanics, Term (time), Long-term memory, Decision Sciences, Automatic Keyword Extraction from Textual Data, FOS: Psychology, Cognition, Artificial Intelligence, Computer Science, Physical Sciences, Information retrieval, Psychology, Textual Data, Text Classification, Natural Language Processing, Neuroscience

TTC-QuAli: A Text-Table-Chart Dataset for Multimodal Quantity Alignment

Autoři: Haoyu Dong Haochen Wang Anda Zhou a další

Zdroj: Proceedings of the 17th ACM International Conference on Web Search and Data Mining. :181-189

Témata: Artificial intelligence, Table (database), Natural language processing, Statistics, Statistical Machine Translation and Natural Language Processing, Computer science, Automatic Keyword Extraction from Textual Data, Database, Artificial Intelligence, 13. Climate action, Computer Science, Physical Sciences, FOS: Mathematics, Information retrieval, Chart, 14. Life underwater, Textual Data, Mathematics, Natural Language Processing