The unified sentiment lexicon using GPUs

Barbosa Santillán, Liliana Ibeth and Alvarez de Mon Rego, Inmaculada ORCID: (2014). The unified sentiment lexicon using GPUs. In: "GPU Technology Conference 2014", 24/03/2014 - 27/03/2014, San Jose, California, EEUU. p. 1.


Title: The unified sentiment lexicon using GPUs
Item Type: Presentation at Congress or Conference (Poster)
Event Title: GPU Technology Conference 2014
Event Dates: 24/03/2014 - 27/03/2014
Event Location: San Jose, California, EEUU
Title of Book: GPU Technology Conference
Date: 2014
Freetext Keywords: Machine Learning & Deep Learning
Faculty: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Department: Lingüistica Aplicada a la Ciencia y a la Tecnología
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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This approach aims at aligning, unifying and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. A sentiment lexicon is a critical and essential resource for tagging subjective corpora on the web or elsewhere. In many situations, the multilingual property of the sentiment lexicon is important because the writer is using two languages alternately in the same text, message or post. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and the UnifiedMetrics procedure for CPU and GPU, respectively.

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Item ID: 36436
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Deposited by: Memoria Investigacion
Deposited on: 30 Mar 2016 19:21
Last Modified: 06 Jun 2016 19:21
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