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When the Easy Becomes Difficult: Factors Affecting the Acquisition of the English /iː/-/ɪ/ Contrast
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In: Frontiers in Communication ; 6 (2022)
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An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
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Calculating semantic relatedness of lists of nouns using WordNet path length ...
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Impact of Sentence Representation Matching in Neural Machine Translation
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1313 (2022)
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The Research on Consistency Checking and Improvement of Probabilistic Linguistic Preference Relation Based on Similarity Measure and Minimum Adjustment Model
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In: Mathematics; Volume 10; Issue 9; Pages: 1369 (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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Capability Language Processing (CLP): Classification and Ranking of Manufacturing Suppliers Based on Unstructured Capability Data
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Usage-Based Contact Linguistics : Effects of Frequency and Similarity in Language Contact
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TSM: Measuring the Enticement of Honeyfiles with Natural Language Processing
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“Language thinking” from the perspective of systemic linguistics
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In: Russian Journal of Linguistics, Vol 26, Iss 1, Pp 224-244 (2022) (2022)
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Automatic Detection of Plagiarism in Writing
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In: Studies in Applied Linguistics & TESOL, Vol 21, Iss 2 (2022) (2022)
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Automatic Detection of Plagiarism in Writing
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In: Studies in Applied Linguistics & TESOL, Vol 21, Iss 2 (2022) (2022)
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Easy-to-use combination of POS and BERT model for domain-specific and misspelled terms
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In: NL4IA Workshop Proceedings ; https://hal.archives-ouvertes.fr/hal-03474696 ; NL4IA Workshop Proceedings, Nov 2021, Milan, Italy (2021)
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Investigating the impact of preprocessing on document embedding: an empirical comparison
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In: ISSN: 1759-1163 ; EISSN: 1759-1171 ; International Journal of Data Mining, Modelling and Management ; https://hal.inrae.fr/hal-03574696 ; International Journal of Data Mining, Modelling and Management, Inderscience, 2021, 13 (4), pp.351-363 (2021)
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Abstract:
International audience ; Digital representation of text documents is a crucial task in machine learning and natural language processing (NLP). It aims to transform unstructured text documents into mathematically-computable elements. In recent years, several methods have been proposed and implemented to encode text documents into fixed-length feature vectors. This operation is known as document embedding and it has become an interesting and open area of research. Paragraph vector (Doc2vec) is one of the most used document embedding methods. It has gained a good reputation thanks to its good results. To overcome its limits, Doc2vec, was extended by proposing the document through corruption (Doc2vecC) technique. To get a deep view of these two methods, this work presents a study on the impact of morphosyntactic text preprocessing on these two document embedding methods. We have done this analysis by applying the most-used text preprocessing techniques, such as cleaning, stemming and lemmatisation, and their different combinations. The experimental analysis on the Microsoft Research Paraphrase dataset (MSRP), reveals that the preprocessing techniques serve to improve the classifier accuracy; and that the stemming method outperforms the other techniques.
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Keyword:
[INFO]Computer Science [cs]; document embedding; document through corruption; natural language preprocessing; paragraph vector; semantic similarity; text preprocessing
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URL: https://hal.inrae.fr/hal-03574696
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Language distance in orthographic transparency affects cross-language pattern similarity between native and non-native languages.
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In: Human brain mapping, vol 42, iss 4 (2021)
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Avoiding gender ambiguous pronouns in French
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-03374279 ; Cognition, Elsevier, 2021 (2021)
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