To Understand the Critical Measures of Enhanced Security in Cloud Computing for Creating Better Data Protection

Lourens, Melanie; Neela, V.; Jambukesh, H J; Khan, Huma; Pant, Bhasker

doi:10.1109/icacite53722.2022.9823425

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…Lack of Corpora and Sentiment lexica, Dialect Diversity, and Code Switching are some significant challenges of Sentiment Analysis in the Arabic Language [9]. [10,11,12,13] determined that other challenges such as spelling, vocabulary, phonetics, and morphology in the Arabic Language increase syntactic, semantic, and figurative ambiguity. Moreover, Realtime sentiment analysis, spam detection, morphological faults, lousy spelling, unstructured data, and implicit meanings are among the challenges of Arabic Sentiment Analysis.…”

Section: Related Workmentioning

confidence: 99%

Kurdish Language Sentiment Analysis: Problems and Challenges

Amin¹

2022

MSEA

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The increasing usage of blogs, social networks, and forums for sharing opinions on a certain topic has created vast amounts of internet data. Therefore, Sentiment Analysis has gained great popularity among researchers and industry for analyzing the polarity of users' opinions. In recent years, Sentiment Analysis has been applied to various languages using machine learning-approach, corpus-based approach, and deep learning techniques since it is beneficial for creating an effective recommender system. The Kurdish Language is an Indo-European language, one of the official languages in Iraq, and it is also widely used in Turkey, Iran, and Syria. Although the importance of this Language is spoken by over 40 million people, to the best of our knowledge, no research has been done regarding the challenges and problems of Kurdish sentiment analysis. Our research aims to highlight the latest studies and examine the most critical challenges of applying sentiment analysis approaches to the Kurdish Language. The study includes determining each challenge in each step of sentiment analysis processing in the Kurdish Language. In addition, our proposed methodology that could help address most of these challenges is implementing a hybrid approach by combining machine learning and lexicon-based approaches to improve the proficiency of sentiment classification in the Kurdish Language.

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Section: Related Workmentioning

confidence: 99%

Kurdish Language Sentiment Analysis: Problems and Challenges

Amin¹

2022

MSEA

View full text Add to dashboard Cite

show abstract

To Understand the Critical Measures of Enhanced Security in Cloud Computing for Creating Better Data Protection

Cited by 1 publication

References 14 publications

Kurdish Language Sentiment Analysis: Problems and Challenges

Kurdish Language Sentiment Analysis: Problems and Challenges

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