Use of Cloud Computing In Higher Education of Pakistan
Kashif Ishaq*,
Adnan Abid,
Shoaib Farooq
et al.
Abstract:Cloud computing is an internet-based service of delivering technology to users and an important technological facility where mutual resources are delivered on demand. Usage of cloud computing in educational Institutions provides students as well as administrative staff an opportunity to access various applications and knowledge swiftly. Its simplicity, upfront-cost, reduced downtime and less management effort make this service acceptable for all fragments of society particularly students and teachers. Despite … Show more
“…In depth, N-gram models were applied with and without stemming categories. Further, the outcomes showed that SVM classifier utilizing TFIDF with stemming inside bigrams features highlight bettered the situation execution [57].…”
By the newly gained attention from several research areas for the field of opinion mining, work in Sentiment Analysis (SA) has also been increased. Sentiment analysis is actually a natural language processing (NLP) method which is implemented to decide whether the data is negative, positive or neutral. This analysis can also utilized to provide most appropriate countermeasures for various issues that are connected with particular fields. It is a contextual extraction and arrangement of text which recognizes and pinpoints subjective information regarding source material and helps to understand the social sentiment of people while monitoring online conversations, comments, tweets, or information on blogs, etc. There is wide utilization of Urdu language in offering perspectives that's why the Urdu language also wants opinion mining as well. In this research, a systematic literature review on sentiment analysis of Urdu language has been performed. This SLR is focusing on explicit research questions and afterward contributions are described appropriately. The findings of the review present a taxonomy that is based on the techniques of sentiment classification. Furthermore, in this SLR, we have extracted all the preprocessing techniques that were used in these 24 papers, the most adopted algorithms by the researchers, the most implemented sentiment analysis approach, and the feature extraction techniques are also extricated. Eventually, a thorough survey is given on all these considerations. After a detailed and deep evaluation, we have computed their accuracy results for better understanding of future researchers.
“…In depth, N-gram models were applied with and without stemming categories. Further, the outcomes showed that SVM classifier utilizing TFIDF with stemming inside bigrams features highlight bettered the situation execution [57].…”
By the newly gained attention from several research areas for the field of opinion mining, work in Sentiment Analysis (SA) has also been increased. Sentiment analysis is actually a natural language processing (NLP) method which is implemented to decide whether the data is negative, positive or neutral. This analysis can also utilized to provide most appropriate countermeasures for various issues that are connected with particular fields. It is a contextual extraction and arrangement of text which recognizes and pinpoints subjective information regarding source material and helps to understand the social sentiment of people while monitoring online conversations, comments, tweets, or information on blogs, etc. There is wide utilization of Urdu language in offering perspectives that's why the Urdu language also wants opinion mining as well. In this research, a systematic literature review on sentiment analysis of Urdu language has been performed. This SLR is focusing on explicit research questions and afterward contributions are described appropriately. The findings of the review present a taxonomy that is based on the techniques of sentiment classification. Furthermore, in this SLR, we have extracted all the preprocessing techniques that were used in these 24 papers, the most adopted algorithms by the researchers, the most implemented sentiment analysis approach, and the feature extraction techniques are also extricated. Eventually, a thorough survey is given on all these considerations. After a detailed and deep evaluation, we have computed their accuracy results for better understanding of future researchers.
“…The paradigm of all domains of life has been rapidly shifting from physical to online means [1]. Education has also been revolutionized with the improvement in technology [2], [3]. Education includes not only learning but also assessment of learning that raise questions about credibility of traditional methods of assessment [4].…”
Educational institutes use different evaluation techniques to assess the learning process of students. This process of assessment in educational institutes is a sensitive issue and traditional evaluation methods often face certain difficulties like cheating, favoritism, political influence etc. Blockchain provides a very important feature of immutability and traceability and helps to manage various issue of online assessments. Once scores have been finalized, they cannot be changed. Every authorized node in the network will have knowledge of evaluation, hence any discrimination would become public. Different researchers have presented assessment models that use blockchain as core technology. To the best of our knowledge, no SLR has been presented till date to discuss educational assessment models using blockchain. This article briefly investigates those models, their working, limitations and performs quality assessment using a scoring criteria. This paper also highlights the research gaps that exist in this domain. Finally, an assessment model has been proposed in this article, to contribute in the domain of online examinational evaluation using blockchain that would help overcoming the limitations that arise in currently existing models.
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