Analysis of book circulation data and a book recommendation system in academic libraries using data mining techniques

Khademizadeh, Shahnaz; Nematollahi, Zahra; Danesh, Farshid

doi:10.1016/j.lisr.2022.101191

Cited by 19 publications

(8 citation statements)

References 20 publications

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“…Jenis penelitian ini ialah deskriptif kualitatif, yakni data penelitian berupa kalimat verbal yang ditelusuri dari berbagai literature dalam berbagai bentuk karya ilmiah. Oleh karenanya, ditinjau dari tempat penelitian ini maka dapat dikategoorikan sebagai library research, yakni peneliti melakukan pengumpulan data dari data-data kepustakaan (Khademizadeh et al, 2022).…”

Section: Methodsunclassified

The Relevance of Mahmud Yunus's Thought to Islamic Education in the Era of Digital Transformation

Badriah

2022

ruhama

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Mahmud Yunus is one of the educational figures from West Sumatra, Indonesia. He was the first rector of IAIN Imam Bonjol Padang. In his lifetime, education with digital technology was not yet known, but the results of his thinking were seen as having relevance to education in the digital era that exists today. Therefore, this study aims to reveal aspects that have relevance between Mahmud Yunus's thoughts and Islamic education in the digital era. This research is a literature review, namely research data collected from literature data both obtained from journals and books as well as the results of the thoughts of academics related to the thoughts of Mahmud Yunus. The results of the research are first, the Concept of Islamic Education Mahmud Yunus's perspective includes the purpose, understanding, content or material, curriculum, methods, educators, and forms of the Islamic educational environment. Second, The relevance of Islamic education according to Mahmud Yunus in the era of digital transformation is in harmony with the existence of religious education and general education and the classification of subject matter is in line with the current classification of education which is closely related to affective, cognitive, and psychomotor aspects. The method does have to adjust the age level of students. And Integration of the curriculum in terms of religious and general sciences. Furthermore, the educational environment influences character building and hones skills and skills so that students have it.

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Section: Methodsunclassified

The Relevance of Mahmud Yunus's Thought to Islamic Education in the Era of Digital Transformation

Badriah

2022

ruhama

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“…Within library and information studies (LIS), recent research considering recommender systems has focused mainly on the technical aspects and on the possibilities for recommender systems in different library settings (Collins et al, 2018;De Nart and Tasso, 2014;Jomsri, 2018;Khademizadeh et al, 2022;Rhanoui et al, 2022;Simovi c, 2018;Yadav and Pervin, 2022), rather than on their role in shaping information practices. However, some recent studies within LIS have focused on AI and algorithms, with major areas of interest being the use and role of search engines in everyday situations (Andersson, 2017(Andersson, , 2021(Andersson, , 2022Sundin, 2019, 2022b;Sundin et al, 2017) and information literacy in relation to algorithms or algorithmic literacy (Lloyd, 2019).…”

Section: Algorithmic Recommendationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Algorithmic recommendations enabling and constraining information practices among young people

Jylhä,

Hirvonen,

Haider

2024

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PurposeThis study addresses how algorithmic recommendations and their affordances shape everyday information practices among young people.Design/methodology/approachThematic interviews were conducted with 20 Finnish young people aged 15–16 years. The material was analysed using qualitative content analysis, with a focus on everyday information practices involving online platforms.FindingsThe key finding of the study is that the current affordances of algorithmic recommendations enable users to engage in more passive practices instead of active search and evaluation practices. Two major themes emerged from the analysis: enabling not searching, inviting high trust, which highlights the how the affordances of algorithmic recommendations enable the delegation of search to a recommender system and, at the same time, invite trust in the system, and constraining finding, discouraging diversity, which focuses on the constraining degree of affordances and breakdowns associated with algorithmic recommendations.Originality/valueThis study contributes new knowledge regarding the ways in which algorithmic recommendations shape the information practices in young people's everyday lives specifically addressing the constraining nature of affordances.

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“…This technology can be applied in many domains, including sales predicting, weather forecasting, and user interest predicting. For example, Khademizadeh et al [10] use the decision tree technique and item-based collaborative filtering algorithm to build a recommender system that analyzes book circulation transactions and identifies user book lending trends. Jiang et al [11] also apply a long short-term memory model and the composite sentiment index to help scholars analyze the energy sector more effectively.…”

Section: Introductionmentioning

confidence: 99%

An e-Learning Recommendation System Framework

Kong,

Haw,

Palanichamy

et al. 2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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With the emergence of the digital era, the e-learning platform has become an effective tool for obtaining quality e-learning content. However, despite its potential, the true extent of its capabilities has yet to be fully explored. In order to attract users and maximize revenue, e-learning platforms are now expected to provide content tailored to their users' needs and preferences. These recommendations are generated by considering factors such as prior purchases, browsing history, demographic information, and more. By leveraging these advanced technologies, e-learning platforms can enhance the learning experience by providing users with content that is both engaging and relevant to their individual needs and interests. This paper explores the popular Machine Learning (ML) techniques employed in e-learning content recommender platforms. Two machine learning techniques, k-Nearest Neighbour Baseline (KNNBaseline) and Singular Value Decomposition (SVD), are selected and used to accurately forecast customer interests and preferences. By examining the data patterns and user behaviors, these ML techniques provide insights into the most relevant and personalized educational content for individual users, enhancing their learning experience. The item ratings predicted are generated based on the underlying pattern in past ratings of users. The performance of applied approaches was assessed using several evaluation metrics, which include root mean square error and mean absolute error.

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Analysis of book circulation data and a book recommendation system in academic libraries using data mining techniques

Cited by 19 publications

References 20 publications

The Relevance of Mahmud Yunus's Thought to Islamic Education in the Era of Digital Transformation

The Relevance of Mahmud Yunus's Thought to Islamic Education in the Era of Digital Transformation

Algorithmic recommendations enabling and constraining information practices among young people

An e-Learning Recommendation System Framework

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