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• W3104092114 abstract "In sentiment analysis, the polarities of the opinions expressed on an object/feature are determined to assess the sentiment of a sentence or document whether it is positive/negative/neutral. Naturally, the object/feature is a noun representation which refers to a product or a component of a product, let us say, the lens in a camera and opinions emanating on it are captured in adjectives, verbs, adverbs and noun words themselves. Apart from such words, other meta-information and diverse effective features are also going to play an important role in influencing the sentiment polarity and contribute significantly to the performance of the system. In this paper, some of the associated information/meta-data are explored and investigated in the sentiment text. Based on the analysis results presented here, there is scope for further assessment and utilization of the meta-information as features in text categorization, ranking text document, identification of spam documents and polarity classification problems." @default.
• W3104092114 created "2020-11-23" @default.
• W3104092114 creator A5039903089 @default.
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• W3104092114 date "2016-06-30" @default.
• W3104092114 modified "2023-10-18" @default.
• W3104092114 title "An New Attractive Mage Technique Using L-Diversity" @default.
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• W3104092114 doi "https://doi.org/10.5121/mlaij.2016.3204" @default.
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