Prediction of Online Lectures Popularity: A Text Mining Approach

Oza, Kavita S.; Naik, Poornima G.

doi:10.1016/j.procs.2016.07.369

Cited by 21 publications

(10 citation statements)

References 7 publications

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“…In this phase, teacher's or student's requests are semantically preprocessed using text mining methods. For automatic text mining, we used R libraries using RStudio for semantic personalized preferences extraction [ 11 , 29 , 32 , 41 ]. Text mining is a type of data mining used to understand and find hidden relations in natural language text semantically [ 11 , 29 , 32 , 41 ].…”

Section: Proposed Systemmentioning

confidence: 99%

“…For automatic text mining, we used R libraries using RStudio for semantic personalized preferences extraction [ 11 , 29 , 32 , 41 ]. Text mining is a type of data mining used to understand and find hidden relations in natural language text semantically [ 11 , 29 , 32 , 41 ]. After the preprocessing, the data is stored in a repository.…”

Section: Proposed Systemmentioning

confidence: 99%

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Enabling remote learning system for virtual personalized preferences during COVID-19 pandemic

Ali

Hafeez

Abbas

et al. 2021

Multimed Tools Appl

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The education system worldwide has been affected by the Corona Virus Diseases 2019 (COVID-19) pandemic, resulting in the interruption of all educational institutions. Moreover, as a precautionary measure, the lockdown has been imposed that has severely affected the learning processes, especially assessment activities, including exams and viva. In such challenging situations, E-learning platforms could play a vital role in conducting seamless academic activities. In spite of all the advantages of remote learning systems, many hurdles and obstacles, like a selection of suitable learning resources/material encounter by individual users based on their interests or requirements. Especially those who are not well familiar with the internet technology in developing countries and are in need of a platform that could help them in resolving the issues related to the online virtual environment. Therefore, in this work, we have proposed a mechanism that intelligently and correctly predicts the appropriate preferences for the selection of resources relevant to a specific user by considering the capabilities of diverse perspectives users to provide quality online education and to make work from home policy more effective and progressive during the pandemic. The proposed system helps teachers in providing quality online education, familiarizing them with advanced technology in the online environment. It also semantically predicts the preferences for virtual assistance of those users who are in need of learning the new tools and technologies in short time as per their institutional requirements in order to meet the quality standards of online education. The experimental and statistical results have demonstrated that the proposed virtual personalized preferences system has improved overall academic activities as compared to the current method. The proposed system enhanced user's learning abilities and facilitated them in selecting short courses while using different online education tools adopted/suggested by the institutions to conduct online classes/seminars/webinars etc., as compared to the conventional classes/activities.

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Section: Proposed Systemmentioning

confidence: 99%

Section: Proposed Systemmentioning

confidence: 99%

Enabling remote learning system for virtual personalized preferences during COVID-19 pandemic

Ali

Hafeez

Abbas

et al. 2021

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…They are more reliable than information provided by sellers because they offer personalized advice as well as ratings of products or services [31]. Many studies have analyzed the relationship between online reviews and product sales for well-known websites such as eBay [32], Amazon [33][34][35], and Airbnb [36,37] and various product categories such as books [33][34][35]38], movies [39][40][41], fashion [42], cosmetics [43], hotels [44][45][46][47], washing machines [48], online lectures [49], restaurants [50,51], and airlines [52].…”

Section: Consumer Car Purchasing Behaviormentioning

confidence: 99%

Analyzing Online Car Reviews Using Text Mining

Kim

Chun

2019

Sustainability

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Consumer reviews on the web have rapidly become an important information source through which consumers can share their experiences and opinions about products and services. It is a form of text-based communication that provides new possibilities and opens vast perspectives in terms of marketing. Reading consumer reviews gives marketers an opportunity to eavesdrop on their own consumers. This paper examines consumer reviews of three different competitive automobile brands and analyzes the advantages and disadvantages of each vehicle using text mining and association rule methods. The data were collected from an online resource for automotive information, Edmunds.com, with a scraping tool “ParseHub” and then processed in R software for statistical computing and graphics. The paper provides detailed insights into the superior and problematic sides of each brand and into consumers’ perceptions of automobiles and highlights differences between satisfied and unsatisfied groups regarding the best and worst features of the brands.

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“…The text-mining tools are being effectively utilized in the interpretation of huge amounts of data in various fields, such as biology, informatics, and education [20,21]. For the purpose of evaluating the benefits of the lectures, text-mining analyses are also used to interpret comments obtained from students objectively [22,23]. This study attempts to analyze the answer sentences in a short answer questionnaire obtained from the students registering the core subject "Evidence of Dietary Education".…”

Section: Evaluation Of the Programmentioning

confidence: 99%

Curricular evaluation of “SHOKUIKU program” as a postgraduate minor course of food and nutrition education using a text-mining procedure

et al. 2018

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Background: "SHOKUIKU", food and nutrition education, is a national promotion to enable people to acquire an adequate knowledge of SHOKU (which include food, nutrition, dietary habits, etc.) in Japanese society and to allow people to make appropriate SHOKU choices in Japan. In order to educate SHOKUIKU experts who can promote evidence-based SHOKUIKU with advanced professional knowledge and skills, an original "SHOKUIKU program" was established. To evaluate this program, a short answer questionnaire was given to students. Results were objectively analyzed by text mining procedures. Methods: Five hundred forty four comment papers submitted by a total of 52 consenting students after each lecture in the 12 omnibus-style lectures were examined as cross-sectional data. A total of 2507 sentences were decomposed into words, and word classes of morpheme in Japanese were properly specified. Subsequently, on the basis of a constructed keyword data base, 123 morphemes with high frequency were investigated with co-occurrence network analysis. Furthermore, multivariate network analyses according to the student's major were performed. Results: Students majoring in food and nutritional sciences recognized that evidence-based SHOKUIKU is "difficult" but "necessary" to "convey" reliable information at "actual" SHOKUIKU sites. On the other hand, students studying other majors not only got an "interesting" opportunity to "learn" "nutrition" and "eating habits" but also thought about their own SHOKUIKU promotion in relation to their major. Conclusions: These results suggest that the students of the Food Course assumed that they would practice the evidence-based SHOKUIKU themselves, while the students of other courses learned new knowledge more passively. The results also confirmed that students comprehensively grasped the 12 omnibus-style lectures and understood the significance of evidence-based SHOKUIKU regardless of their major. Our original educational program could be valuable for postgraduate students to promote SHOKUIKU.

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Prediction of Online Lectures Popularity: A Text Mining Approach

Cited by 21 publications

References 7 publications

Enabling remote learning system for virtual personalized preferences during COVID-19 pandemic

Enabling remote learning system for virtual personalized preferences during COVID-19 pandemic

Analyzing Online Car Reviews Using Text Mining

Curricular evaluation of “SHOKUIKU program” as a postgraduate minor course of food and nutrition education using a text-mining procedure

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