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Between History and Natural Language Processing: Study, Enrichment and Online Publication of French Parliamentary Debates of the Early Third Republic (1881-1899)
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In: ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora ; https://hal.archives-ouvertes.fr/hal-03623351 ; ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora, Jun 2022, Marseille, France ; https://www.clarin.eu/ParlaCLARIN-III (2022)
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Chinese-Uyghur Bilingual Lexicon Extraction Based on Weak Supervision
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In: Information; Volume 13; Issue 4; Pages: 175 (2022)
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Investigating the Efficient Use of Word Embedding with Neural-Topic Models for Interpretable Topics from Short Texts
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In: Sensors; Volume 22; Issue 3; Pages: 852 (2022)
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Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 9; Pages: 5705 (2022)
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An Enhanced Neural Word Embedding Model for Transfer Learning
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In: Applied Sciences; Volume 12; Issue 6; Pages: 2848 (2022)
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Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2694 (2022)
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Predicting Academic Performance: Analysis of Students’ Mental Health Condition from Social Media Interactions
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In: Behavioral Sciences; Volume 12; Issue 4; Pages: 87 (2022)
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Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022)
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Methods, Models and Tools for Improving the Quality of Textual Annotations
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In: Modelling; Volume 3; Issue 2; Pages: 224-242 (2022)
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Abstract:
In multilingual textual archives, the availability of textual annotation, that is keywords either manually or automatically associated with texts, is something worth exploiting to improve user experience and successful navigation, search and visualization. It is therefore necessary to study and develop tools for this exploitation. The paper aims to define models and tools for handling textual annotations, in our case keywords of a scientific library. With the background of NLP, machine learning and deep learning approaches are presented. They allow us, in supervised and unsupervised ways, to increase the quality of keywords. The different steps of the pipeline are addressed, and different solutions are analyzed, implemented, evaluated and compared, using statistical methods, machine learning and artificial neural networks as appropriate. If possible, off-the-shelf solutions will also be compared. The models are trained on different datasets already available or created ad hoc with common characteristics with the starting dataset. The results obtained are presented, commented and compared with each other.
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Keyword:
LSTM; machine learning algorithms; multilingual datasets; neural networks; semantic relatedness; sequence2sequence; syntactic similarity; word embedding models
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URL: https://doi.org/10.3390/modelling3020015
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Creating multi-scripts sentiment analysis lexicons for Algerian, Moroccan and Tunisian dialects
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In: 7th International Conference on Data Mining (DTMN 2021) Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) ; https://hal.archives-ouvertes.fr/hal-03308111 ; 7th International Conference on Data Mining (DTMN 2021) Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT), Sep 2021, Copenhagen, Denmark (2021)
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Bilingual English-German word embedding models for scientific text ...
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Bilingual English-German word embedding models for scientific text ...
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以《Cofacts 真的假的》資料庫為基礎建立中文科學假訊息之探勘模型 ; Text Mining Model for Detecting Chinese Fake Scientific Messages based on Cofacts Open Data
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Automatic Part-of-Speech Tagging for Security Vulnerability Descriptions ...
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Automatic Part-of-Speech Tagging for Security Vulnerability Descriptions ...
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Text ranking based on semantic meaning of sentences ; Textrankning baserad på semantisk betydelse hos meningar
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Efficient Estimate of Low-Frequency Words’ Embeddings Based on the Dictionary: A Case Study on Chinese
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In: Applied Sciences ; Volume 11 ; Issue 22 (2021)
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Acoustic Word Embeddings for End-to-End Speech Synthesis
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In: Applied Sciences ; Volume 11 ; Issue 19 (2021)
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