Results for 'Security in Data Mining'

975 found
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  1. 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 (...)
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  2.  42
    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 (...)
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  3.  20
    Study on data mining method of network security situation perception based on cloud computing.Rahul Neware, Vishal Jagota, Arshpreet Kaur & Yan Zhang - 2022 - Journal of Intelligent Systems 31 (1):1074-1084.
    In recent years, the network has become more complex, and the attacker’s ability to attack is gradually increasing. How to properly understand the network security situation and improve network security has become a very important issue. In order to study the method of extracting information about the security situation of the network based on cloud computing, we recommend the technology of knowledge of the network security situation based on the data extraction technology. It converts each (...)
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    Research on data mining method of network security situation awareness based on cloud computing.Rajan Miglani, Abdullah M. Baqasah, Roobaea Alroobaea, Guodong Zhao & Ying Zhou - 2022 - Journal of Intelligent Systems 31 (1):520-531.
    Due to the complexity and versatility of network security alarm data, a cloud-based network security data extraction method is proposed to address the inability to effectively understand the network security situation. The information properties of the situation are generated by creating a set of spatial characteristics classification of network security knowledge, which is then used to analyze and optimize the processing of hybrid network security situation information using cloud computing technology and co-filtering technology. (...)
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  5. 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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  6.  16
    Construction of Social Security Fund Cloud Audit Platform Based on Fuzzy Data Mining Algorithm.Yangting Huai & Qianxiao Zhang - 2021 - Complexity 2021:1-11.
    Guided by the theories of system theory, synergetic theory, and other disciplines and based on fuzzy data mining algorithm, this article constructs a three-tier social security fund cloud audit platform. Firstly, the article systematically expounds the current situation of social security fund and social security fund audit, such as the technical basis of cloud computing and data mining. Combined with the actual work, the necessity and feasibility of building a cloud audit platform for (...)
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  7.  12
    Intelligent terminal security technology of power grid sensing layer based upon information entropy data mining.Zhibin Yang, Gang Wang, Shuheng Xu, Yaodong Tao, Defeng Chen & Shuai Ren - 2022 - Journal of Intelligent Systems 31 (1):817-834.
    The power grid is an important connection between power sources and users, responsible for supplying and distributing electric energy to users. Modern power grids are widely distributed and large in scale, and their security faces new problems and challenges. Information entropy theory is an objective weighting method that compares the information order of each evaluation index to judge the weight value. With the wide application of entropy theory in various disciplines, the subject of introducing entropy into the power system (...)
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  8. Moral Implications of Data-Mining, Key-word Searches, and Targeted Electronic Surveillance.Michael Skerker - 2015 - In Bradley J. Strawser, Fritz Allhoff & Adam Henschke, 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 (...)
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  9.  23
    Visual Mining Method of Japanese Movie Resources Based on Association Rules.Qin Wang - 2023 - European Journal for Philosophy of Religion 15 (4):419-435.
    One of the crucial fields of study that is getting more attention is association rule mining. It is crucial to databases' knowledge discovery (KDD). KDD and association rule mining have a very broad use. It has evolved at a rapid rate over the past fifteen years. Association Rule Mining is a novel technology, although it is still in the discovery and development stages. Video is an illustration of interactive media data since it contains text, pictures, meta- (...), visual, sound, and different kinds of data. It is frequently used for a variety of important likely reasons, such as security and reconnaissance, amusement, healthcare, educational endeavours, and sports. One of the main issues for the local data-mining research community is video data mining, which aims to find and comprehend fascinating examples from the large volume of video data. Video data mining is still in its infancy when compared to mining other sorts of data. It is pivotal to grasp and naturally mine the information from video databases considering the continually extending computerized libraries and video databases. Differentiating association rules between components in a significant video library is critical in the field of video data mining. As per continuous imaginative work, association rule mining is being utilized rapidly in various tasks, including perception, social affairs, broadcast news, sports, records, films, clinical data, as well as on the web and individual media assortments. This exploration tries to give a far-reaching method to association rule extraction from video databases. (shrink)
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  10.  11
    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 (...)
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  11. 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, Lecture Notes In Computer Science. Springer Verlag. pp. 713-720.
  12.  9
    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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  13. 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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  14.  21
    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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  15. 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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  16. 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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  17. 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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  18.  21
    (1 other version)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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  19. 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, Lecture Notes In Computer Science. Springer Verlag. pp. 779-788.
     
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  20.  38
    Temporal data mining for educational applications.Carole R. Beal & Paul R. Cohen - 2008 - In Tu-Bao Ho & Zhi-Hua Zhou, PRICAI 2008: Trends in Artificial Intelligence. Springer. pp. 66--77.
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  21. Data Mining the Brain to Decode the Mind.Daniel Weiskopf - 2020 - In Fabrizio Calzavarini & Marco Viola, Neural Mechanisms: New Challenges in the Philosophy of Neuroscience. Springer.
    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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  22.  18
    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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  23.  40
    A case study on human development and security: Madagascar's mining sector and conservation-induced displacement of populations.Jérôme Ballet & Mahefasoa Randrianalijaona - 2014 - Journal of Global Ethics 10 (2):216-230.
    This case study introduces the QIT Madagascar Minerals (QMM) SA mining project at Fort-Dauphin, Madagascar, as a development project that has produced issues concerning justice. Although QMM appears to be a model company with a project that is seen as a success story, its consequent displacement of populations has been problematic in many respects, as have been the social effects that arise due to migration to the area by others who are attracted by the project. We suggest that the (...)
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  24.  42
    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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  25.  43
    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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  26.  41
    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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  27.  27
    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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  28. 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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  29. (1 other version)Ontology-assisted database integration to support natural language processing and biomedical data-mining.Jean-Luc Verschelde, Marianna C. Santos, Tom Deray, Barry Smith & Werner Ceusters - 2004 - Journal of Integrative Bioinformatics. Repr. In: Yearbook of Bioinformatics , 39–48 1:1-10.
    Successful biomedical data mining and information extraction require a complete picture of biological phenomena such as genes, biological processes, and diseases; as these exist on different levels of granularity. To realize this goal, several freely available heterogeneous databases as well as proprietary structured datasets have to be integrated into a single global customizable scheme. We will present a tool to integrate different biological data sources by mapping them to a proprietary biomedical ontology that has been developed for (...)
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  30. A Framework Proposal for Developing Historical Video Games Based on Player Review Data Mining to Support Historic Preservation.Sarvin Eshaghi, Sepehr Vaez Afshar & Mahyar Hadighi - 2023 - In Saif Haq, Adil Sharag-Eldin & Sepideh Niknia, ARCC 2023 CONFERENCE PROCEEDING: The Research Design Interface. Architectural Research Centers Consortium, Inc.. pp. 297-305.
    Historic preservation, which is a vital act for conveying people’s understanding of the past, such as events, ideas, and places to the future, allows people to preserve history for future generations. Additionally, since the historic properties are currently concentrated in urban areas, an urban-oriented approach will contribute to the issue. Hence, public awareness is a key factor that paves the way for this conservation. Public history, a history with a public audience and special methods of representation, can serve society in (...)
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  31.  20
    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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  32.  27
    Use of Official Data of State Institutions in the Scientific Research of the Population Security.Vidmantas Egidijus Kurapka & Viktoras Justickis - 2010 - Jurisprudencija: Mokslo darbu žurnalas 121 (3):283-294.
    The paper discusses the problems in the detection of security information in legal and other administrative data. The authors analyse the prospects of the use of datamining in the solution of two key problems: abundance and indirectness of these data. Security research uses two kinds of data. The first one is scientific data, designed and gathered specially for the verification of certain security theories. They are the data of criminological, sociological, psychological surveys, (...)
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  33. (Abstract) Using Linguistics Corpus Data Analysis to Combat PRC's Cognitive Infiltration.Jr-Jiun Lian - 2024 - 2024 Annual Conference of the Communication Association: International Academic Conference on Communication and Democratic Resilience.
    In light of Taiwan's extensive exposure to the Chinese Communist Party's "cognitive domain infiltration warfare," this paper proposes new response mechanisms and strategies for cybersecurity and national defense. The focus is primarily on assessing the CCP's cognitive infiltration tactics to develop policy recommendations in cybersecurity linguistics. These recommendations are intended to serve as a reference for future national defense and information security policies. Within the constraints of limited resources, this study attempts to provide an integrated analysis method combining qualitative (...)
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  34.  44
    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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  35.  42
    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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  36. Part VI-Risk Management Systems with Intelligent Data Analysis-Implementing an Integrated Time-Series Data Mining Environment Based on Temporal Pattern Extraction Methods: A Case Study of an.Hidenao Abe, Miho Ohsaki, Hideto Yokoi & Takahira Yamaguchi - 2006 - In O. Stock & M. Schaerf, Lecture Notes In Computer Science. Springer Verlag. pp. 425-435.
     
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  37.  15
    Identification of Factors Associated With School Effectiveness With Data Mining Techniques: Testing a New Approach.Fernando Martínez-Abad - 2019 - Frontiers in Psychology 10:494763.
    The study of school effectiveness and the identification of factors associated with it are growing fields of research in the education sciences. Moreover, from the perspective of data mining, great progress has been made in the development of algorithms for the modeling and identification of non-trivial information from massive databases. This work, which falls within this context, proposes an innovative approach for the identification and characterization of educational and organizational factors associated with high school effectiveness. Under a perspective (...)
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  38.  85
    All that glitters is not gold: Digging beneath the surface of data mining[REVIEW]Anthony Danna & Oscar H. Gandy - 2002 - Journal of Business Ethics 40 (4):373 - 386.
    This article develops a more comprehensive understanding of data mining by examining the application of this technology in the marketplace. In addition to exploring the technological issues that arise from the use of these applications, we address some of the social concerns that are too often ignored.As more firms shift more of their business activities to the Web, increasingly more information about consumers and potential customers is being captured in Web server logs. Sophisticated analytic and data (...) software tools enable firms to use the data contained in these logs to develop and implement a complex relationship management strategy. Although this new trend in marketing strategy is based on the old idea of relating to customers as individuals, customer relationship management actually rests on segmenting consumers into groups based on profiles developed through a firm's data mining activities. Individuals whose profiles suggest that they are likely to provide a high lifetime value to the firm are served content that will vary from that which is served to consumers with less attractive profiles. (shrink)
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  39.  28
    Known or knowing publics? Social media data mining and the question of public agency.Giles Moss & Helen Kennedy - 2015 - Big Data and Society 2 (2).
    New methods to analyse social media data provide a powerful way to know publics and capture what they say and do. At the same time, access to these methods is uneven, with corporations and governments tending to have best access to relevant data and analytics tools. Critics raise a number of concerns about the implications dominant uses of data mining and analytics may have for the public: they result in less privacy, more surveillance and social discrimination, (...)
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  40. Identifying Virtues and Values Through Obituary Data-Mining.Mark Alfano, Andrew Higgins & Jacob Levernier - 2018 - Journal of Value Inquiry 52 (1).
    Because obituaries are succinct and explicitly intended to summarize their subjects’ lives, they may be expected to include only the features that the author finds most salient but also to signal to others in the community the socially-recognized aspects of the deceased’s character. We begin by reviewing studies 1 and 2, in which obituaries were carefully read and labeled. We then report study 3, which further develops these results with a semi-automated, large-scale semantic analysis of several thousand obituaries. Geography, gender, (...)
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  41.  42
    Unlocking data: Where is the key?María C. Sánchez & Antonio Sarría‐Santamera - 2019 - Bioethics 33 (3):367-376.
    Health‐related data uses and data sharing have been in the spotlight for a while. Since the beginning of the big data era, massive data mining and its inherent possibilities have only increased the debate about what the limits are. Data governance is a relevant aspect addressed in ethics guidelines. In this context, the European project BRIDGE Health (BRidging Information and Data Generation for Evidence‐based Health policy and research) strove to achieve a comprehensive, integrated (...)
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  42.  32
    Living Multiples: How Large-scale Scientific Data-mining Pursues Identity and Differences.Adrian Mackenzie & Ruth McNally - 2013 - Theory, Culture and Society 30 (4):72-91.
    This article responds to two problems confronting social and human sciences: how to relate to digital data, inasmuch as it challenges established social science methods; and how to relate to life sciences, insofar as they produce knowledge that impinges on our own ways of knowing. In a case study of proteomics, we explore how digital devices grapple with large-scale multiples – of molecules, databases, machines and people. We analyse one particular visual device, a cluster-heatmap, produced by scientists by (...) data from a large number of experiments on human blood plasma proteins. These proteins make up a myriad multiple whose identity shifts in many ways. Rather than displaying data about proteins, the heatmap constructs a view of the differences and similarities between experiments. We find this attempt to construct a view on many things at once instructive in thinking about multiples more generally. Instead of flattening molecular ‘life itself’, this visual device superimposes layers of digital devices and techniques from a wide variety of disciplines. This layering suggests a different way of relating to the life sciences more generally: rather than what they know, how they know might be of use to social and human sciences when attending to multiplicities. (shrink)
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  43. Measuring the process of quality of care for ST‐segment elevation acute myocardial infarction through datamining of the electronic discharge notes.Sheng-Nan Chang, Jou-Wei Lin, Shi-Chi Liu & Juey-Jen Hwang - 2008 - Journal of Evaluation in Clinical Practice 14 (1):116-120.
  44.  87
    Decision support systems for police: Lessons from the application of data mining techniques to “soft” forensic evidence. [REVIEW]Giles Oatley, Brian Ewart & John Zeleznikow - 2006 - Artificial Intelligence and Law 14 (1-2):35-100.
    The paper sets out the challenges facing the Police in respect of the detection and prevention of the volume crime of burglary. A discussion of data mining and decision support technologies that have the potential to address these issues is undertaken and illustrated with reference the authors’ work with three Police Services. The focus is upon the use of “soft” forensic evidence which refers to modus operandi and the temporal and geographical features of the crime, rather than “hard” (...)
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  45. (1 other version)Mapping Human Values: Enhancing Social Marketing through Obituary Data-Mining.Mark Alfano, Andrew Higgins & Jacob Levernier - forthcoming - In Lynn Kahle & Eda Atay, Social and Cultural Values in a Global and Digital Age.
  46. Topic 5-Parallel and Distributed Databases, Data Mining and Knowledge Discovery-Supporting a Real-Time Distributed Intrusion Detection Application on GATES.Qian Zhu, Liang Chen & Gagan Agrawal - 2006 - In O. Stock & M. Schaerf, Lecture Notes In Computer Science. Springer Verlag. pp. 4128--360.
     
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  47.  54
    Better decision support through exploratory discrimination-aware data mining: foundations and empirical evidence.Bettina Berendt & Sören Preibusch - 2014 - Artificial Intelligence and Law 22 (2):175-209.
    Decision makers in banking, insurance or employment mitigate many of their risks by telling “good” individuals and “bad” individuals apart. Laws codify societal understandings of which factors are legitimate grounds for differential treatment —or are considered unfair discrimination, including gender, ethnicity or age. Discrimination-aware data mining implements the hope that information technology supporting the decision process can also keep it free from unjust grounds. However, constraining data mining to exclude a fixed enumeration of potentially discriminatory features (...)
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    Distribution of Large-Scale English Test Scores Based on Data Mining.Na Chu & Wanzhi Ma - 2021 - Complexity 2021:1-10.
    Data mining technology is an effective knowledge mining and data relationship induction technology based on massive data, which is widely used in data analysis in many fields. In order to improve the utilization effect of students’ performance and meet the teaching needs of modern education, data mining technology can be applied to the existing performance database to mine the data information and treatment. Data mining technology is used to analyse (...)
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    Predicting insurance claims through a variety of data mining techniques: facing lots of missing values and moderate class-imbalanced levels.Paola Santana-Morales & Antonio J. Tallón-Ballesteros - forthcoming - Logic Journal of the IGPL.
    This paper copes with a real-world classification problem related to the management of claims received in an insurance company. The way to obtain the classifier is not easy due to the high amount of missing values as well as the inherent imbalanced scenario within class labels. Once the data partition has been done, the training set is submitted to an intensive double grid search in order to obtain the most promising type of missing value imputation approach and then a (...)
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    Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm.Hongyan Wang - 2021 - Complexity 2021:1-11.
    This paper presents the concept and algorithm of data mining and focuses on the linear regression algorithm. Based on the multiple linear regression algorithm, many factors affecting CET4 are analyzed. Ideas based on data mining, collecting history data and appropriate to transform, using statistical analysis techniques to the many factors influencing the CET-4 test were analyzed, and we have obtained the CET-4 test result and its influencing factors. It was found that the linear regression relationship (...)
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