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1
Sentiment Lexicon Construction Using SentiWordNet 3.0
Whalley, JL; Medagoda, N. - : IEEE, 2015
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2
Improving the performance of an example-based machine translation system using a domain-specific bilingual lexicon
In: 29th Pacific Asia Conference on Language, Information and Computation, PACLIC 2015 ; https://hal-cea.archives-ouvertes.fr/cea-01844060 ; 29th Pacific Asia Conference on Language, Information and Computation, PACLIC 2015, Oct 2015, Shangai, China. pp.106-115 (2015)
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3
Evaluating the impact of using a domain-specific bilingual lexicon on the performance of a hybrid machine translation approach
In: 10th International Conference on Recent Advances in Natural Language Processing, RANLP 201 ; https://hal-cea.archives-ouvertes.fr/cea-01844051 ; 10th International Conference on Recent Advances in Natural Language Processing, RANLP 201, Sep 2015, Hissar, Bulgaria. pp.579-587 (2015)
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4
Whicht lexicon for which emotions in FFL's classroom ? ; Quel lexique pour quelles émotions en classe de FLE ?
In: ISSN: 0458-7251 ; Le Langage et l'Homme ; https://hal.archives-ouvertes.fr/hal-01375964 ; Le Langage et l'Homme, EME éditions / L'Harmattan, 2015, Affects et acquisition des langues, L.2 (50/2), pp.115-128 ; https://www.intercommunications.be/fr/41_le-langage-et-l-homme (2015)
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5
CRIS Cyber Range Lexicon, Version 1.0
In: DTIC (2015)
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6
Legislative Lexicon ; Research Spotlight
Texas. Legislature. Senate. Research Center.. - : Texas. Legislature. Senate. Research Center., 2015
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7
Sentiment analysis over social networks: an overview
Ahmed, K.; Tazi, N.; Hossny, A.. - : IEEE, 2015
Abstract: The rapid increase in data on social media creates a need for mining such data to get valuable insights. The data type can be unstructured with large volumes. Sentiment analysis addresses such need by detecting opinions or emotions on the social media text. Sentiment analysis can be performed in various domains such as social, medical and industrial applications. This paper presents a survey about sentiment analysis addressing the different concepts in this area, problems and its solutions, available APIs, tools used and presenting a list of open challenges in this area. ; Khaled Ahmed, Neamat El Tazi, Ahmad Hany Hossny
Keyword: feature selection; recommendation; sentiment analysis; Sentiment lexicons and emotion detection; social media; spam detection
URL: https://doi.org/10.1109/SMC.2015.380
http://hdl.handle.net/2440/108776
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