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1
Demo of the Linguistic Field Data Management and Analysis System -- LiFE ...
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2
Unsupervised Learning of Explainable Parse Trees for Improved Generalisation ...
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3
The ComMA Dataset V0.2: Annotating Aggression and Bias in Multilingual Social Media Discourse ...
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4
Towards automatic identification of linguistic politeness in Hindi texts ...
Kumar, Ritesh. - : arXiv, 2021
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5
More Than Smell-COVID-19 Is Associated With Severe Impairment of Smell, Taste, and Chemesthesis.
In: Chemical senses, vol 45, iss 7 (2020)
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6
More than smell. COVID-19 is associated with severe impairment of smell, taste, and chemesthesis
In: ISSN: 0379-864X ; EISSN: 1464-3553 ; Chemical Senses ; https://hal.inrae.fr/hal-02911030 ; Chemical Senses, Oxford University Press (OUP), 2020, 45 (7), pp.609-622. ⟨10.1093/chemse/bjaa041⟩ ; https://academic.oup.com/chemse/article/doi/10.1093/chemse/bjaa041/5860460 (2020)
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7
NUIG-Panlingua-KMI Hindi-Marathi MT Systems for Similar Language Translation Task @ WMT 2020
Chakravarthi, Bharathi Raja; Kumar, Ritesh; Rani, Priya. - : Association for Computational Linguistics, 2020
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8
Developing a Multilingual Annotated Corpus of Misogyny and Aggression ...
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9
More Than Smell-COVID-19 Is Associated With Severe Impairment of Smell, Taste, and Chemesthesis
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10
More than smell – COVID-19 is associated with severe impairment of smell, taste, and chemesthesis
In: Chem Senses (2020)
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11
More than smell - COVID-19 is associated with severe impairment of smell, taste, and chemesthesis
Parma, Valentina; Ohla, Kathrin; Veldhuizen, Maria G.. - : Oxford University Press, 2020
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12
Predicting the Type and Target of Offensive Posts in Social Media ...
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13
Predicting the Type and Target of Offensive Posts in Social Media
In: 1415 ; 1420 (2019)
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14
Automatic Identification of Closely-related Indian Languages: Resources and Experiments ...
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15
Understanding the Odour Spaces ... : A Step towards Solving Olfactory Stimulus-Percept Problem ...
Kumar, Ritesh; Kaur, Rishemjit; Auffarth, Benjamin. - : Freie Universität Berlin, 2015
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16
Understanding the Odour Spaces: A Step towards Solving Olfactory Stimulus-Percept Problem
Kumar, Ritesh; Kaur, Rishemjit; Auffarth, Benjamin; Bhondekar, Amol P.. - : Public Library of Science, 2015
Abstract: Odours are highly complex, relying on hundreds of receptors, and people are known to disagree in their linguistic descriptions of smells. It is partly due to these facts that, it is very hard to map the domain of odour molecules or their structure to that of perceptual representations, a problem that has been referred to as the Structure-Odour-Relationship. We collected a number of diverse open domain databases of odour molecules having unorganised perceptual descriptors, and developed a graphical method to find the similarity between perceptual descriptors; which is intuitive and can be used to identify perceptual classes. We then separately projected the physico-chemical and perceptual features of these molecules in a non-linear dimension and clustered the similar molecules. We found a significant overlap between the spatial positioning of the clustered molecules in the physico-chemical and perceptual spaces. We also developed a statistical method of predicting the perceptual qualities of a novel molecule using its physico-chemical properties with high receiver operating characteristics(ROC).
Keyword: Research Article
URL: http://www.ncbi.nlm.nih.gov/pubmed/26484763
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615634/
https://doi.org/10.1371/journal.pone.0141263
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