Results for 'data mining'

991 found
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  1.  30
    Comparing assessments of the decision-making competencies of psychiatric inpatients as provided by physicians, nurses, relatives and an assessment tool.Rahime Er & Mine Sehiralti - 2014 - Journal of Medical Ethics 40 (7):453-457.
    Objective To compare assessments of the decision-making competencies of psychiatric inpatients as provided by physicians, nurses, relatives and an assessment tool.Methods This study was carried out at the psychiatry clinic of Kocaeli University Hospital from June 2007 to February 2008. The decision-making competence of the 83 patients who participated in the study was assessed by physicians, nurses, relatives and MacCAT-T.Results Of the 83 patients, the relatives of 73.8% of them, including the parents of 47.7%, were interviewed during the study. A (...)
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  2.  7
    A Transactional Or A Relational Contract? The Student Consumer, Social Participation And Alumni Donations In Higher Education.Manuel Souto-Otero, Michael Donnelly & Mine Kanol - 2024 - British Journal of Educational Studies 72 (1):85-107.
    The relationship between students and higher education is seen to have become increasingly transactional. We approach the study of the student–HE relationship in a novel way, by focusing on students’ behaviour post-university, rather than on student narratives. Conceptually, the article builds on multidimensional views of student engagement and the differentiation between psychological transactional contracts – where students who achieve better academic results are more likely to donate – and relational contracts – where students donate more following engagement in social experiences. (...)
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  3. Data mining to combat terrorism and the roots of privacy concerns.Frans A. J. Birrer - 2005 - Ethics and Information Technology 7 (4):211-220.
    Recently, there has been a heavy debate in the US about the government’s use of data mining in its fight against terrorism. Privacy concerns in fact led the Congress to terminate the funding of TIA, a program for advanced information technology to be used in the combat of terrorism. The arguments put forward in this debate, more specifically those found in the main report and minority report by the TAPAC established by the Secretary of Defense to examine the (...)
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  4.  85
    Data Mining and Privacy of Social Network Sites’ Users: Implications of the Data Mining Problem.Yeslam Al-Saggaf & Md Zahidul Islam - 2015 - Science and Engineering Ethics 21 (4):941-966.
    This paper explores the potential of data mining as a technique that could be used by malicious data miners to threaten the privacy of social network sites users. It applies a data mining algorithm to a real dataset to provide empirically-based evidence of the ease with which characteristics about the SNS users can be discovered and used in a way that could invade their privacy. One major contribution of this article is the use of the (...)
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  5. Data-mining probabilists or experimental determinists.Thomas Richardson, Laura Schulz & Alison Gopnik - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press. pp. 208--230.
  6. Retractions Data Mining #1.Quan-Hoang Vuong & Viet-Phuong La - 2019 - Open Science Framework 2019 (2):1-3.
    Motivation: • Breaking barriers in publishing demands a proactive attitude • Open data, open review and open dialogue in making social sciences plausible .
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  7.  32
    Temporal data mining for educational applications.Carole R. Beal & Paul R. Cohen - 2008 - In Tu-Bao Ho & Zhi-Hua Zhou (eds.), Pricai 2008: Trends in Artificial Intelligence. Springer. pp. 66--77.
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  8. Data Mining, Retrieval and Management-An Interactive Hybrid System for Identifying and Filtering Unsolicited E-mail.M. Dolores del Castillo & J. Ignacio Serrano - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer Verlag. pp. 779-788.
     
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  9. Data mining and group profiling on the Internet.B. H. M. Custers - 2001 - In Anton Vedder (ed.), Ethics and the Internet. Intersentia.
  10. Symposium: Data Mining.Roger E. Backhouse - 2000 - Journal of Economic Methodology 7 (2):171-277.
  11.  4
    Using Data Mining Approach for Student Satisfaction With Teaching Quality in High Vocation Education.Bailin Chen, Yi Liu & Jinqiu Zheng - 2022 - Frontiers in Psychology 12.
    High vocation education is an important foundation for China to cultivate high teaching quality and technical and skilled talents. In the new era, the acceleration of the development of modern vocational education is put in a more prominent position. It is proposed that we should adhere to moral education, closely combine this with the needs of technological change and industrial upgrading, constantly improve the quality of high vocational education teaching, and cultivate more technical and skilled talents with both political integrity (...)
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  12. Data Mining the Brain to Decode the Mind.Daniel Weiskopf - forthcoming - In Neural Mechanisms: New Challenges in the Philosophy of Neuroscience.
    In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I argue (...)
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  13. KDD, data mining, and the challenge for normative privacy.Herman T. Tavani - 1999 - Ethics and Information Technology 1 (4):265-273.
    The present study examines certain challenges that KDD (Knowledge Discovery in Databases) in general and data mining in particular pose for normative privacy and public policy. In an earlier work (see Tavani, 1999), I argued that certain applications of data-mining technology involving the manipulation of personal data raise special privacy concerns. Whereas the main purpose of the earlier essay was to show what those specific privacy concerns are and to describe how exactly those concerns have (...)
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  14.  84
    Data mining: Proprietary rights, people and proposals.Dinah Payne & Cherie Courseault Trumbach - 2009 - Business Ethics, the Environment and Responsibility 18 (3):241-252.
    This article focuses on the issue of data mining as it relates to the consumer and to the issue of whether the consumer's private information has any proprietary status. A brief review of data mining is provided as a background for a better understanding of the purposes and uses of data mining. Also examined are several issues of the ethics of data mining, including a review of stakeholders, who they are and which (...)
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  15.  36
    Data mining: proprietary rights, people and proposals.Dinah Payne & Cherie Courseault Trumbach - 2009 - Business Ethics: A European Review 18 (3):241-252.
    This article focuses on the issue of data mining as it relates to the consumer and to the issue of whether the consumer's private information has any proprietary status. A brief review of data mining is provided as a background for a better understanding of the purposes and uses of data mining. Also examined are several issues of the ethics of data mining, including a review of stakeholders, who they are and which (...)
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  16.  25
    Phenomenal Data Mining: From Observations to Phenomena.John McCarthy - unknown
    • Conventional data mining infers relations among e.g. the fraction of supermarket baskets with diapers also contain beer. • Phenomenal data mining concerns relations between data and the phenomena underlying the data, e.g. y married couples keeping old friends buy diapers and • Example: The sales receipts of a supermarket usually not identify the customers. Grouping baskets by customer is possible and useful but requires new techniques.
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  17.  9
    Educational Data Mining Techniques for Student Performance Prediction: Method Review and Comparison Analysis.Yupei Zhang, Yue Yun, Rui An, Jiaqi Cui, Huan Dai & Xuequn Shang - 2021 - Frontiers in Psychology 12.
    Student performance prediction aims to evaluate the grade that a student will reach before enrolling in a course or taking an exam. This prediction problem is a kernel task toward personalized education and has attracted increasing attention in the field of artificial intelligence and educational data mining. This paper provides a systematic review of the SPP study from the perspective of machine learning and data mining. This review partitions SPP into five stages, i.e., data collection, (...)
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  18.  7
    Data Mining Approach Improving Decision-Making Competency along the Business Digital Transformation Journey: A Case Study – Home Appliances after Sales Service.Hyrmet Mydyti - 2021 - Seeu Review 16 (1):45-65.
    Data mining, as an essential part of artificial intelligence, is a powerful digital technology, which makes businesses predict future trends and alleviate the process of decision-making and enhancing customer experience along their digital transformation journey. This research provides a practical implication – a case study - to provide guidance on analyzing information and predicting repairs in home appliances after sales services business. The main benefit of this practical comparative study of various classification algorithms, by using the Weka tool, (...)
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  19.  18
    Prescription Data Mining and the Protection of Patients' Interests.David Orentlicher - 2010 - Journal of Law, Medicine and Ethics 38 (1):74-84.
    Pharmaceutical companies have exploited health information technology to “mine” data from drug prescriptions and use the data to better target their sales pitches to physicians. This article considers the policy arguments and first amendment implications regarding state regulation of data mining. It concludes that the legislative provisions are desirable and should withstand constitutional challenge.
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  20.  12
    Data mining applications in university information management system development.Ashima Kukkar, Amit Sharma, Juntao Fan & Minshun Zhang - 2022 - Journal of Intelligent Systems 31 (1):207-220.
    Nowadays, the modern management is promoted to resolve the issue of unreliable information transmission and to provide work efficiency. The basic aim of the modern management is to be more effective in the role of the school to train talents and serve the society. This article focuses on the application of data mining (DM) in the development of information management system (IMS) in universities and colleges. DM provides powerful approaches for a variety of educational areas. Due to the (...)
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  21.  86
    Secure and Scalable Data Mining Technique over a Restful Web Services.Solar Francesco & Oliver Smith - forthcoming - International Journal of Research and Innovation in Applied Science.
    Scalability, efficiency, and security had been a persistent problem over the years in data mining, several techniques had been proposed and implemented but none had been able to solve the problem of scalability, efficiency and security from cloud computing. In this research, we solve the problem scalability, efficiency and security in data mining over cloud computing by using a restful web services and combination of different technologies and tools, our model was trained by using different machine (...)
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  22.  18
    Data Mining Techniques in Analyzing Process Data: A Didactic.Xin Qiao & Hong Jiao - 2018 - Frontiers in Psychology 9.
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  23.  16
    Data Mining and Hypothesis Refinement using a Multi-Tiered Genetic Algorithm.C. M. Taylor & A. Agah - 2010 - Journal of Intelligent Systems 19 (3):191-226.
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  24. Moral Implications of Data-Mining, Key-word Searches, and Targeted Electronic Surveillance.Michael Skerker - 2015 - In Bradley J. Strawser, Fritz Allhoff & Adam Henschke (eds.), Binary Bullets.
    This chapter addresses the morality of two types of national security electronic surveillance (SIGINT) programs: the analysis of communication “metadata” and dragnet searches for keywords in electronic communication. The chapter develops a standard for assessing coercive government action based on respect for the autonomy of inhabitants of liberal states and argues that both types of SIGINT can potentially meet this standard. That said, the collection of metadata creates opportunities for abuse of power, and so judgments about the trustworthiness and competence (...)
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  25.  99
    Genomic research and data-mining technology: Implications for personal privacy and informed consent.Herman T. Tavani - 2004 - Ethics and Information Technology 6 (1):15-28.
    This essay examines issues involving personal privacy and informed consent that arise at the intersection of information and communication technology and population genomics research. I begin by briefly examining the ethical, legal, and social implications program requirements that were established to guide researchers working on the Human Genome Project. Next I consider a case illustration involving deCODE Genetics, a privately owned genetics company in Iceland, which raises some ethical concerns that are not clearly addressed in the current ELSI guidelines. The (...)
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  26.  35
    Using data-mining to identify and study patterns in lexical innovation on the web.Daphné Kerremans, Jelena Prokić, Quirin Würschinger & Hans-Jörg Schmid - 2018 - Pragmatics and Cognition 25 (1):174-200.
    This paper presents the NeoCrawler – a tailor-made webcrawler, which identifies and retrieves neologisms from the Internet and systematically monitors the use of detected neologisms on the web by means of weekly searches. It enables researchers to use the web as a corpus in order to investigate the dynamics of lexical innovation on a large-scale and systematic basis. The NeoCrawler represents an innovative web-mining tool which opens up new opportunities for linguists to tackle a number of unresolved and under-researched (...)
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  27.  4
    Intelligent Data Mining of Computer-Aided Extension Residential Building Design Based on Algorithm Library.Gao Zhihui & Zou Guangtian - 2021 - Complexity 2021:1-9.
    In recent years, with the development of construction industry, more scientific, systematic, fast, and intelligent calculation methods are needed to coordinate urban development and fierce market competition, and mathematical algorithm library plays an important role in artificial intelligence. Therefore, the author uses computer mathematical algorithm and extension theory to study and analyze the residential building design and intelligent data mining. It is found that the research of the computer-aided expression method of extension building planning is mainly the expression (...)
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  28. Ethical issues in web data mining.Lita van Wel & Lambèr Royakkers - 2004 - Ethics and Information Technology 6 (2):129-140.
    Web mining refers to the whole of data miningand related techniques that are used toautomatically discover and extract informationfrom web documents and services. When used in abusiness context and applied to some type ofpersonal data, it helps companies to builddetailed customer profiles, and gain marketingintelligence. Web mining does, however, pose athreat to some important ethical values likeprivacy and individuality. Web mining makes itdifficult for an individual to autonomouslycontrol the unveiling and dissemination of dataabout his/her private (...)
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  29.  33
    Data Mining the Intellectual Revival of 'Catastrophic' Mother Nature.Nick Marriner & Christophe Morhange - 2013 - Foundations of Science 18 (2):245-257.
    Earth-shaping catastrophic events have long focused the attention of the geographical and geological sciences, and captured the public imagination. During the past 40 years, neocatastrophism has emerged as a key paradigm that reflects widespread changes involving cultural, scientific, political and technological spheres. Nonetheless, the extent, chronology and origin of this trend are equivocal. Here, we use Google Ngram to quantitatively explore the recent development of catastrophism. We elucidate a discernable rise in neocatastrophic thinking during the last quarter of the twenty-first (...)
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  30.  13
    Multi-Data Mining for Understanding Leadership Behavior.Naohiro Matsumura & Yoshihiro Sasaki - 2008 - In S. Iwata, Y. Oshawa, S. Tsumoto, N. Zhong, Y. Shi & L. Magnani (eds.), Communications and Discoveries From Multidisciplinary Data. Springer. pp. 81--94.
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  31.  6
    Análisis mediante Data Mining de comentarios paulinos de Tomás de Aquino.Enrique Alarcón Moreno - 2021 - Studium Filosofía y Teología 24 (48):27-38.
    Data Mining es una tecnología de estadística computarizada para la extracción de pautas reiteradas y significativas a partir de datos cuantiosos. En este artículo se exponen primero los fundamentos para su aplicación al análisis de los textos. Después, se detalla la aplicación del análisis de afinidad a buena parte de los escritos de Tomás de Aquino. Y, finalmente, se muestran los resultados obtenidos del análisis de varios de sus comentarios paulinos.
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  32. Data Mining, Retrieval and Management-Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes.Honghai Feng, Hao Xu, Baoyan Liu, Bingru Yang, Zhuye Gao & Yueli Li - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer Verlag. pp. 713-720.
  33.  8
    Prescription Data Mining and the Protection of Patients' Interests.David Orentlicher - 2010 - Journal of Law, Medicine and Ethics 38 (1):74-84.
    Pharmaceutical companies have long relied on direct marketing of their drugs to physicians through one-on-one meetings with sales representatives. This practice of “detailing” is substantial in its costs and its number of participants. Every year, pharmaceutical companies spend billions of dollars on millions of visits to physicians by tens of thousands of sales representatives.Critics have argued that drug detailing results in sub-optimal prescribing decisions by physicians, compromising patient health and driving up spending on medical care. In this view, physicians often (...)
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  34.  14
    Data Mining in the Mixed Methods: Application to the Study of the Psychological Profiles of Athletes.José L. Pastrana, Rafael E. Reigal, Verónica Morales-Sánchez, Juan P. Morillo-Baro, Rocío Juárez-Ruiz de Mier, José Alves & Antonio Hernández-Mendo - 2019 - Frontiers in Psychology 10.
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  35.  29
    Data Mining and the Privatization of Accountability.Edward Tverdek - 2006 - Public Affairs Quarterly 20 (1):67-94.
  36.  13
    Data Mining for Evolving Fuzzy Association Rules for Predicting Monsoon Rainfall of India.C. T. Dhanya & D. Nagesh Kumar - 2009 - Journal of Intelligent Systems 18 (3):193-210.
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  37. Informational privacy, data mining, and the internet.Herman T. Tavani - 1999 - Ethics and Information Technology 1 (2):137-145.
    Privacy concerns involving data mining are examined in terms of four questions: What exactly is data mining? How does data mining raise concerns for personal privacy? How do privacy concerns raised by data mining differ from those concerns introduced by traditional information-retrieval techniques in computer databases? How do privacy concerns raised by mining personal data from the Internet differ from those concerns introduced by mining such data from (...) warehouses? It is argued that the practice of using data-mining techniques, whether on the Internet or in data warehouses, to gain information about persons raises privacy concerns that go beyond concerns introduced in traditional information-retrieval techniques in computer databases and are not covered by present data-protection guidelines and privacy laws. (shrink)
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  38.  7
    Application of data mining technology in detecting network intrusion and security maintenance.Mehedi Masud, Roobaea Alroobaea, Fahad M. Almansour, Gurjot Singh Gaba & Yongkuan Zhu - 2021 - Journal of Intelligent Systems 30 (1):664-676.
    In order to correct the deficiencies of intrusion detection technology, the entire computer and network security system are needed to be more perfect. This work proposes an improved k-means algorithm and an improved Apriori algorithm applied in data mining technology to detect network intrusion and security maintenance. The classical KDDCUP99 dataset has been utilized in this work for performing the experimentation with the improved algorithms. The algorithm’s detection rate and false alarm rate are compared with the experimental (...) before the improvement. The outcomes of proposed algorithms are analyzed in terms of various simulation parameters like average time, false alarm rate, absolute error as well as accuracy value. The results show that the improved algorithm advances the detection efficiency and accuracy using the designed detection model. The improved and tested detection model is then applied to a new intrusion detection system. After intrusion detection experiments, the experimental results show that the proposed system improves detection accuracy and reduces the false alarm rate. A significant improvement of 90.57% can be seen in detecting new attack type intrusion detection using the proposed algorithm. (shrink)
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  39.  7
    Data Mining Algorithm for Demand Forecast Analysis on Flash Sales Platform.Mingyang Zhang, Yixin Wang & Zhiguo Wu - 2021 - Complexity 2021:1-12.
    With the development of the digital economy, the emerging marketing strategy of the e-commerce flash sales has been changing the traditional purchasing habits of customers. This imposes new decision-making challenges for companies involved in flash sales. It is important for companies to build the accurate product demand forecast analysis focusing on the characteristics of the flash sales and customer behaviors. In this paper, VIPS is taken as a case study with the key focus on how sentiment factors in customer reviews (...)
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  40.  16
    Use of Data Mining to Determine Usage Patterns of an Online Evaluation Platform During the COVID-19 Pandemic.Rafael E. Reigal, José Luis Pastrana-Brincones, Sergio Luis González-Ruiz, Antonio Hernández-Mendo, Juan Pablo Morillo-Baro & Verónica Morales-Sánchez - 2020 - Frontiers in Psychology 11.
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  41.  30
    The Use of Data Mining by Private Health Insurance Companies and Customers’ Privacy.Yeslam Al-Saggaf - 2015 - Cambridge Quarterly of Healthcare Ethics 24 (3):281-292.
    :This article examines privacy threats arising from the use of data mining by private Australian health insurance companies. Qualitative interviews were conducted with key experts, and Australian governmental and nongovernmental websites relevant to private health insurance were searched. Using Rationale, a critical thinking tool, the themes and considerations elicited through this empirical approach were developed into an argument about the use of data mining by private health insurance companies. The argument is followed by an ethical analysis (...)
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  42.  23
    Apriori Algorithm for the Data Mining of Global Cyberspace Security Issues for Human Participatory Based on Association Rules.Zhi Li, Xuyu Li, Runhua Tang & Lin Zhang - 2021 - Frontiers in Psychology 11.
    This study explored the global cyberspace security issues, with the purpose of breaking the stereotype of people’s cognition of cyberspace problems, which reflects the relationship between interdependence and association. Based on the Apriori algorithm in association rules, a total of 181 strong rules were mined from 40 target websites and 56,096 web pages were associated with global cyberspace security. Moreover, this study analyzed support, confidence, promotion, leverage, and reliability to achieve comprehensive coverage of data. A total of 15,661 sites (...)
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  43.  30
    The Use of Data Mining Methods to Predict the Result of Infertility Treatment Using the IVF ET Method.Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewska, Jan Czerniecki & Sławomir Wołczyński - 2014 - Studies in Logic, Grammar and Rhetoric 39 (1):67-74.
    The IVF ET method is a scientifically recognized infertility treat- ment method. The problem, however, is this method’s unsatisfactory efficiency. This calls for a more thorough analysis of the information available in the treat- ment process, in order to detect the factors that have an effect on the results, as well as to effectively predict result of treatment. Classical statistical methods have proven to be inadequate in this issue. Only the use of modern methods of data mining gives (...)
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  44.  16
    Privacy concerns in educational data mining and learning analytics.Isak Potgieter - 2020 - International Review of Information Ethics 28.
    Education at all levels is increasingly augmented and enhanced by data mining and analytics, catalysed by the growing prevalence of automated distance learning. With an unprecedented capacity to scale both horizontally and vertically, data mining and analytics are set to be a transformative part of the future of education. We reflect on the assumptions behind data mining and the potential consequences of learning analytics, with reference to an issue brief prepared for the U.S. Department (...)
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  45.  14
    Text and Data Mining in Directive 2019/790/EU Enhancing Web-Harvesting and Web-Archiving in Libraries and Archives.Μaria Bottis, Marinos Papadopoulos, Christos Zampakolas & Paraskevi Ganatsiou - 2019 - Open Journal of Philosophy 9 (3):369-395.
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  46.  20
    From radioactivity to data mining: Günther Anders in the Anthropocene.Christopher John Müller - 2019 - Thesis Eleven 153 (1):9-23.
    This essay traces the complex constellation of ideas that informs Anders's turn to the generalizing expression ‘the human’ in his postwar work. It mobilizes the properties of radioactive material and digital data, which are both curiously imperceptible to our senses, to discuss Anders’s insistence on the universalizing pronoun `we' and assess its significance in the contemporary world. To do so, it aligns Anders's work with current debates about the Anthropocene and critiques of the use of the term ‘the human’ (...)
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  47. Categorized and integrated data mining of clinical data.Akinori Abe, Norihiro Hagita, Michiko Furutani, Yoshiyuki Furutani & Rumiko Matsuoka - 2008 - In S. Iwata, Y. Oshawa, S. Tsumoto, N. Zhong, Y. Shi & L. Magnani (eds.), Communications and Discoveries From Multidisciplinary Data. Springer. pp. 315-330.
     
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  48.  6
    Using Selected Data-Mining Methods in the Analysis of Data Concerning the Attitudes of Students towards the Issue of Vaccination.Anna Justyna Milewska, Karolina Milewska & Marcin Milewski - 2021 - Studies in Logic, Grammar and Rhetoric 66 (3):549-559.
    Preventive vaccination is one of the greatest successes of modern medicine. The SARS-CoV-2 epidemic, during which vaccination is the main method of prevention against death and severe disease, gave rise to a resurgence of anti-vaccine movements. The aim of this study was to analyse the attitudes of students towards vaccination and the COVID-19 pandemic. The statistical analysis was performed with the use of the following data-mining methods: correspondence analysis and basket analysis. The obtained results show that students of (...)
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  49.  14
    Applying Educational Data Mining to Explore Viewing Behaviors and Performance With Flipped Classrooms on the Social Media Platform Facebook.Yu-Sheng Su & Chin-Feng Lai - 2021 - Frontiers in Psychology 12.
    In recent years, learning materials have gradually been applied to flipped classrooms. Teachers share learning materials, and students can preview the learning materials before class. During class, the teacher can discuss students' questions from their notes from previewing the learning materials. The social media platform Facebook provides access to learning materials and diversified interactions, such as sharing knowledge, annotating learning materials, and establishing common objectives. Previous studies have explored the effect of flipped classrooms on students' learning engagement, attitudes, and performance. (...)
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  50.  9
    Application of data mining technology in college mental health education.Xiaocong Sun - 2022 - Frontiers in Psychology 13.
    In order to improve education and teaching methods and meet the “heart” needs of college students in the era of big data, this paper analyzes the application of data mining technology in college mental health education, and introduces database technology and decision tree algorithm to support college mental health work. This process verifies the feasibility of this kind of system with the help of an example. Using the test standards outlined in this document, 1.5 previous test tasks (...)
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