General Depiction of An Efficient Bootstrapper :A Review
By: Qadir, Rabiya
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Contributor(s): Khan, Afaq Alam.
Publisher: New Delhi STM Journals 2019Edition: Vol.6(3), Sep-Dec.Description: 9-12p.Subject(s): Computer EngineeringOnline resources: Click here
In:
Journal of artificial intelligence research and advances (JoAIRA)Summary: Abstract: Bootstrapping is a technique which can automatically annotate emotional corpora. It is a pre-eminent job aimed by many companies who want to research the sentiments of products before purchase, or many companies that want to observe a view or opinion that is held or expressed by public about their brands. The significance of this research is expressed by the fact that, in the present era, people’s emotions has a very great importance for business, politics and for people also. So, there arises a need to create a technique which can create emotional corpus and using this resource emotion detection, systems can work in the best possible manner with the least waste of time and effort. In this paper, different techniques and approaches are discussed given by different researchers to create an efficient bootstrapper for automatic annotation of data. This paper also presents the results that were recorded in the different experiments by various researchers.
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School of Engineering & Technology Archieval Section | Not for loan | 2021121 |
Abstract: Bootstrapping is a technique which can automatically annotate emotional corpora. It is a pre-eminent job aimed by many companies who want to research the sentiments of products before purchase, or many companies that want to observe a view or opinion that is held or expressed by public about their brands. The significance of this research is expressed by the fact that, in the present era, people’s emotions has a very great importance for business, politics and for people also. So, there arises a need to create a technique which can create emotional corpus and using this resource emotion detection, systems can work in the best possible manner with the least waste of time and effort. In this paper, different techniques and approaches are discussed given by different researchers to create an efficient bootstrapper for automatic annotation of data. This paper also presents the results that were recorded in the different experiments by various researchers.
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