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Complete Variable-Length Codes: An Excursion into Word Edit Operations
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In: LATA 2020 ; https://hal.archives-ouvertes.fr/hal-02389403 ; LATA 2020, Mar 2020, Milan, Italy (2020)
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Apprentissage de plongements de mots sur des corpus en langue de spécialité : une étude d’impact
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In: Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 3 : Rencontre des Étudiants Chercheurs en Informatique pour le TAL ; 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 3 : Rencontre des Étudiants Chercheurs en Informatique pour le TAL ; https://hal.archives-ouvertes.fr/hal-02786198 ; 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 3 : Rencontre des Étudiants Chercheurs en Informatique pour le TAL, Jun 2020, Nancy, France. pp.164-178 (2020)
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Unsupervised cross-lingual representation modeling for variable length phrases ; Apprentissage de représentations cross-lingue d’expressions de longueur variable
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In: https://hal.archives-ouvertes.fr/tel-02938554 ; Computation and Language [cs.CL]. Université de Nantes, 2020. English (2020)
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Word Representations Concentrate and This is Good News!
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In: CoNLL 2020 - 24th Conference on Computational Natural Language Learning ; https://hal.univ-grenoble-alpes.fr/hal-03356609 ; CoNLL 2020 - 24th Conference on Computational Natural Language Learning, Association for Computational Linguistics (ACL), Nov 2020, Online, France. pp.325-334, ⟨10.18653/v1/2020.conll-1.25⟩ (2020)
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Implementing Eco’s Model Reader with WordEmbeddings. An Experiment on Facebook Ideological Bots
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In: JADT - Journées d'analyse des données textuelles ; https://hal.archives-ouvertes.fr/hal-03144105 ; JADT - Journées d'analyse des données textuelles, Jun 2020, Toulouse, France (2020)
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Natural language understanding in argumentative dialogue systems ...
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Automatic Creation of Correspondence Table of Meaning Tags from Two Dictionaries in One Language Using Bilingual Word Embedding
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ArAutoSenti: Automatic annotation and new tendencies for sentiment classification of Arabic messages
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French AXA Insurance Word Embeddings : Effects of Fine-tuning BERT and Camembert on AXA France’s data
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Zouari, Hend. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020
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Entropy-Based Approach for the Detection of Changes in Arabic Newspapers’ Content
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In: Entropy ; Volume 22 ; Issue 4 (2020)
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A Framework for Word Embedding Based Automatic Text Summarization and Evaluation
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In: Information ; Volume 11 ; Issue 2 (2020)
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Abstract:
Text summarization is a process of producing a concise version of text (summary) from one or more information sources. If the generated summary preserves meaning of the original text, it will help the users to make fast and effective decision. However, how much meaning of the source text can be preserved is becoming harder to evaluate. The most commonly used automatic evaluation metrics like Recall-Oriented Understudy for Gisting Evaluation (ROUGE) strictly rely on the overlapping n-gram units between reference and candidate summaries, which are not suitable to measure the quality of abstractive summaries. Another major challenge to evaluate text summarization systems is lack of consistent ideal reference summaries. Studies show that human summarizers can produce variable reference summaries of the same source that can significantly affect automatic evaluation metrics scores of summarization systems. Humans are biased to certain situation while producing summary, even the same person perhaps produces substantially different summaries of the same source at different time. This paper proposes a word embedding based automatic text summarization and evaluation framework, which can successfully determine salient top-n sentences of a source text as a reference summary, and evaluate the quality of systems summaries against it. Extensive experimental results demonstrate that the proposed framework is effective and able to outperform several baseline methods with regard to both text summarization systems and automatic evaluation metrics when tested on a publicly available dataset.
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Keyword:
Automatic evaluation metrics; extrinsic evaluation; intrinsic evaluation; natural language processing; text summarization; word embedding
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URL: https://doi.org/10.3390/info11020078
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Data from: Wide range screening of algorithmic bias in word embedding models using large sentiment lexicons reveals underreported bias types ...
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Early Vedic – Morphosyntactic structures, Part 3 ... : Word Order, Embedding ...
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Keydana, Götz. - : Georg-August-Universität Göttingen,Sprachwissenschaftliches Seminar, 2020
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COMBINING TEXT EMBEDDING WITH ADDITIONAL KNOWLEDGE FOR INFORMATION EXTRACTION ...
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Roy, Arpita. - : Maryland Shared Open Access Repository, 2020
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Assessing Topical Homogeneity with Word Embedding and Distance Matrices
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In: School of Information Studies - Faculty Scholarship (2020)
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Quantum-like generalization of complex word embedding: a lightweight approach for textual classification.
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USE OF WORD EMBEDDING TO GENERATE SIMILAR WORDS AND MISSPELLINGS FOR TRAINING PURPOSE IN CHATBOT DEVELOPMENT
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