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Journal articles on the topic 'Datamini'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Bresseel, Joachim, and Kawin Jiaranaisakul. "Pylaemenes scrupeus sp. nov., a new Datamini from Thailand (Phasmida: Heteropterygidae: Dataminae)." Belgian Journal of Entomology 123 (December 31, 2018): 1–15. https://doi.org/10.5281/zenodo.13271771.

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Bresseel, Joachim, Jiaranaisakul, Kawin (2018): Pylaemenes scrupeus sp. nov., a new Datamini from Thailand (Phasmida: Heteropterygidae: Dataminae). Belgian Journal of Entomology 123: 1-15, DOI: 10.5281/zenodo.13271771

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2

Bresseel, Joachim, and Jérôme Constant. "Microrestes gen. nov., a new genus in the Oriental stick insect tribe Datamini Rehn & Rehn, 1939 with a new species and a new combination (Phasmida: Heteropterygidae: Dataminae)." Belgian Journal of Entomology 106 (November 27, 2020): 1–19. https://doi.org/10.5281/zenodo.13590307.

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Bresseel, Joachim, Constant, Jérôme (2020): Microrestes gen. nov., a new genus in the Oriental stick insect tribe Datamini Rehn & Rehn, 1939 with a new species and a new combination (Phasmida: Heteropterygidae: Dataminae). Belgian Journal of Entomology 106: 1-19, DOI: 10.5281/zenodo.13590307

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3

Gao, Hao-Ran, and Chong-Xin Xie. "Pylaemenes gulinqingensis sp. nov., a new species of subfamily Dataminae (Phasmida, Heteropterygidae) from Yunnan Province, China." Journal of Orthoptera Research 31, no. (2) (2022): 125–29. https://doi.org/10.3897/jor.31.79783.

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Pylaemenes gulinqingensis sp. nov., from Gulinqing Nature Reserve, Maguan County, Yunnan, China, is described for the first time from two females and six eggs. The types of the new species are deposited in Southwest Forestry University (SWFU), China, as well as in the first author's collection.

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4

Liu, Yi-Fan, Jun-Jie Gu, and Hai-Jian Wang. "Genus Hainanphasma Ho, 2013: taxonomic notes and two new species from Hainan in China (Phasmida, Heteropterygidae)." ZooKeys 1232 (March 25, 2025): 357–78. https://doi.org/10.3897/zookeys.1232.140688.

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Two new species of <i>Hainanphasma</i> Ho, 2013, <i>Hainanphasma longiacuta</i> sp. nov. and <i>H. longidentata</i> sp. nov., are described and illustrated based on specimens of both sexes from Hainan, China. The heads of <i>H. cristata</i> Ho, 2013, based on both sexes, and <i>H. diaoluoshanensis</i> Ho, 2013, based on females, are redescribed from new materials. The generic diagnosis of <i>Hainanphasma</i> is improved, and the distinction from <i>Orestes</i> Redtenbacher, 1906 is clarified. The male and egg of <i>H. diaoluoshanensis</i> are described and illustrated for the first time. A key

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5

Faye, Fatou, and Mbaye Sene. "Datamining Tool: Multiple Regression and Logistic Regression in a Web Platform of a Datawarehouse." Advanced Materials Research 694-697 (May 2013): 2299–307. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.2299.

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This article summarizes the works about the design of a datamining tool based on statistical methods (Multiple Regression and Logistic Regression). Dataminig [1] is a science which uses mathematical and statistical methods to highlight the links hidden between two or several different variables. This science helps the leaders in their forecasts and in their decision-making. Among the numerous statistical methods used by datamining, only the multiple regression and the logistic regression are objects of a complete study in this work. Indeed, the Multiple Regression is the first mathematical met

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6

Imielinski, T., and A. Virmani. "DataMine—interactive rule discovery system." ACM SIGMOD Record 24, no. 2 (1995): 472. http://dx.doi.org/10.1145/568271.223885.

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7

Wang, Dong Yun, and Zhi Jun Ren. "The Solution of Datamining Based on Clementine." Advanced Materials Research 211-212 (February 2011): 1082–86. http://dx.doi.org/10.4028/www.scientific.net/amr.211-212.1082.

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Datamining used by an enterprise is an powerful tool to provide quickly our enterprise useful information and improve well our decision making . Based on clementine, the paper has given a solution of datamining, has certain innovation, higher theoretical significance and practical value. This paper mainly researches how to build a datamining application based on clementine.

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8

D N, Ashwini, and Soumya Dass B. "Role of Data Mining Technique: A Boon to Society." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 657–60. http://dx.doi.org/10.22214/ijraset.2022.43782.

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Abstract: Datamining is a method of finding interested patterns from huge volume of data. Datamining techniques helps to make business decisions. It analyses information from multiple sources like DataMart, databases. In this paper, we are focussing on datamining tasks and its variety of applications in different fields, which is boon to the society. Keywords: KDD, Decision Tree, OLAP servers, Cube API, ODBC, Frequent patterns

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9

Brieva, Jorge. "Datamining and Its Applications." Journal of Artificial Intelligence and Technology 2, no. 3 (2022): 77–79. http://dx.doi.org/10.37965/jait.2022.0125.

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   Artificial intelligence and machine learning are widely applied in all domain applications today, including noncontact vital sign monitoring, data mining and denoising, data analysis, and application as traffic simulation and green finance. We briefly introduce the noncontact vital sign monitoring using video data and the solutions to this problem supplied by Artificial intelligence and machine learning. Then, we present the five papers selected in the related areas for this journal issue.  

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10

Van Aartsen, Carina. "Grootse plannen met datamining." Zorgvisie ICT 19, no. 3 (2018): 30–32. http://dx.doi.org/10.1007/s41186-018-0111-6.

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11

Howe, J. H. "The application of DATAMINE in kaolin resource management." Geological Society, London, Special Publications 63, no. 1 (1992): 143–48. http://dx.doi.org/10.1144/gsl.sp.1992.063.01.14.

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12

Collins, J. L. "Evaluating pit designs through DATAMINE-GUIDE mining software." International Journal of Surface Mining, Reclamation and Environment 9, no. 3 (1995): 121–24. http://dx.doi.org/10.1080/09208119508964731.

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13

Jordão, Vilma Rodrigues, Sandra Gama, and Daniel Gonçalves. "Visualizing Sequential Educational Datamining Patterns." International Journal of Creative Interfaces and Computer Graphics 7, no. 1 (2016): 1–18. http://dx.doi.org/10.4018/ijcicg.2016010101.

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The use of educational datamining techniques to elicit patterns in student behavior and learning outcomes can be a useful for the analysis of the effectiveness of teaching strategies and the coordination of study programs. However, results from those techniques are, often, large sets of symbolic patterns, numbering in the thousands, usually presented in text format. This makes them hard to understand which, coupled with the lack of an overall view, hinders a more comprehensive data analysis. The authors propose that information visualization techniques can be used to display relevant informati

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14

IMAI, Hiroshi. "Datamining from the Infermation Contents." Journal of the Society of Mechanical Engineers 109, no. 1056 (2006): 874–76. http://dx.doi.org/10.1299/jsmemag.109.1056_874.

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15

Mahalakshmi, Dr J., J. Pradeep Kumar, and T. Jayasri. "Weather Forecasting Using Datamining Techniques." International Journal for Research in Applied Science and Engineering Technology 12, no. 9 (2024): 459–62. http://dx.doi.org/10.22214/ijraset.2024.64206.

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Weather forecasting in particular locations now heavily rely on the application of scientific and technical developments. Recognizing observable patterns, like the association between red sunsets and fine weather, was a prerequisite for early weather forecasting techniques. These forecasts varied in their accuracy, nevertheless. In an effort provide accurate forecasts, modern weather forecasting now considers factors including temperature, humidity and wind. Ascribed to the tremendous impact that environmental degradation has on society meteorology—the field that investigates weather forecasti

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16

van Aartsen, Carina. "Datamining is het nieuwe licht." Zorgvisie 48, no. 5 (2018): 26–29. http://dx.doi.org/10.1007/s41187-018-0070-3.

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17

Hendri, Hendri, and Dony Oscar. "PENERAPAN ALGORITMA C4.5 DALAM MENGUKUR KEPUASAN PENGUNJUNG TERHADAP FASILITAS DI TAMAN MARGASATWA JAKARTA." Jurnal Infortech 3, no. 1 (2021): 73–78. http://dx.doi.org/10.31294/infortech.v3i1.10504.

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Penelitian ini bertujuan untuk memberi rekomendasi kepuasan pengunjung taman taman margasatwa dengan menggunakan teknik datamining penerapan datamining C4.5. Sumber data diperoleh dari penyebaran kuesioner kepada pengnjung yang pernah berkunjung ke taman margasatwa kepada 35 orang. Atribut yang digunakan sebagai parameter penilaian kepuasan pengunjung antara lain: Paling Diminati,Fasilitas Semuah,Tempat parkir , Keamanan, dan Kebersihan . Hasil pengolahan metode C4.5 dengan menggunakan Pohon keputusan adalah model prediksi menggunakan struktur pohon atau struktur berhirarki.

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18

Ha, Jun-Su, Chae Hwan Lim, Kwang-Hee Cho, and Hun-Koo Ha. "Forecasting the Daily Container Volumes Using Data Mining with CART Approach." Journal of Korea Port Economic Association 37, no. 3 (2021): 1–17. http://dx.doi.org/10.38121/kpea.2021.09.37.3.1.

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19

MIN, Kyung-Chang, and Hun-Koo HA. "Forecasting the Daily Demand of Air Cargo Using Data Mining with CHAID Approach." Journal of Korean Society of Transportation 38, no. 3 (2020): 190–207. http://dx.doi.org/10.7470/jkst.2020.38.3.190.

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20

Et. al., G. Ravi Kumar,. "Security and Privacy Protection in Datamining." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (2021): 1313–18. http://dx.doi.org/10.17762/turcomat.v12i2.1218.

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Security and Privacy protection have been a public approach worry for quite a long time. Notwithstanding, quick innovative changes, the fast development of the internet and electronic business, and the improvement of more modern techniques for gathering, investigating, and utilizing individual information have made privacy a significant public and government issues. The field of data mining is acquiring importance acknowledgment to the accessibility of a lot of data, effortlessly gathered and put away through PC systems. Data mining procedures, while permitting the people to remove shrouded in

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21

Parameswari, Uma. "Survey on Unsupervised Learning in Datamining." IOSR Journal of Computer Engineering 14, no. 1 (2013): 46–53. http://dx.doi.org/10.9790/0661-1414653.

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22

K. Sindhu, K., and B. B. Meshram. "Digital Forensics and Cyber Crime Datamining." Journal of Information Security 03, no. 03 (2012): 196–201. http://dx.doi.org/10.4236/jis.2012.33024.

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23

Lustigova, Zdena, and P. Brom. "Educational Datamining in Virtual Learning Environments." International Journal of Advanced Corporate Learning (iJAC) 7, no. 1 (2014): 39. http://dx.doi.org/10.3991/ijac.v7i1.3557.

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24

BÁNKUTI, Gyöngyi. "Artificial Intelligence methods available in meat and milk production." Acta agriculturae Slovenica. Suplement, no. 31 (October 1, 2001): 323–27. http://dx.doi.org/10.14720/aas-s.2001.31.19507.

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A synopsis of modern Artificial Intelligence (AI) methods: knowledge based systems and datamining is giving in the paper. Knowledge based systems can be used in any phase of meat and milk production. If we collect professional information, rules, events, customs and we use the presented methods (programs), we can make an expert advisory system. Datamining is a very young special field of AI. It can “mine” new, unknown information from large databases, without having a hypothesis. In the bibliography not only titles of books but Internet addresses and available journals one listed as well.

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25

FIR, (Institute for Industrial Management) at RWTH Aachen University. "DATAMITE: An Innovative Platform for Monetising Data." UdZ / Issue 01.24 The Data-driven Enterprise 2024, no. 1 (2024): 42–47. https://doi.org/10.5281/zenodo.14228689.

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26

Nugroho, Kristiawan, Wiwien Hadi Kurniawati, and Raden Mohamad Herdian Bhakti. "Perancangan Sales Prediction Model Menggunakan Metode Neural Network." Jurnal Ilmiah Intech : Information Technology Journal of UMUS 4, no. 02 (2022): 153–60. http://dx.doi.org/10.46772/intech.v4i02.870.

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Datamining merupakan fenomena penting pada bidang ilmu teknologi informasi yang telah membantu manusia pada berbagai bidang kehidupan. Datamining merupakan bidang ilmu yang menarik untuk diteliti apalagi pada saat ini dimana Big Data yang dihaslilkan dalam berbagai kehidupan manusia mempunyai volume yang sangat besar namun kurang memberikan arti bagi kehidupan. Penelitian datamining mengenai sales prediction memberikan kontribusi positif bagi para pengambil keputusan dalam melakukan prediksi penjualan barang yang dilakukan secara online berdasarkan beberapa fitur antara lain usia,jenis kelamin

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27

Veeramalai, S., Mr T. Praveen, and S. Pradeepa Natarajan. "Cost Based On Product Quality Prediction Using Datamining." International Journal of Trend in Scientific Research and Development Special Issue, Special Issue-Active Galaxy (2018): 38–42. http://dx.doi.org/10.31142/ijtsrd14564.

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28

Naqa, Issam El, Joseph O. Deasy, Yi Mu, et al. "Datamining approaches for modeling tumor control probability." Acta Oncologica 49, no. 8 (2010): 1363–73. http://dx.doi.org/10.3109/02841861003649224.

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29

Chalupová, Naděžda. "Prediction of customer behaviour through datamining assets." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 57, no. 3 (2009): 43–54. http://dx.doi.org/10.11118/actaun200957030043.

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Business managers accounting for commercial success or non-success of the organization have to gain knowledge needful for correct decision acceptance. These knowledge represent sophisticated information hidden in enterprise data. One possibility, how to extract mentioned knowledge from data, is to use so-called datamining assets.The paper deals with an application of chosen basic methods of knowledge discovering in databases for area of customer-provider relation and it presents, how to avail acquired knowledge as basis of managerial decisions leading to improving of customer relationship m

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30

T. Aghayev, Firudin, Gulara A. Mammadova, Rena T. Malikova, and Lala A. Zeynalova. "Optimization of Curriculum Content Using DataMining Methods." International Journal of Education and Management Engineering 14, no. 4 (2024): 15–22. http://dx.doi.org/10.5815/ijeme.2024.04.02.

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31

Obayashi, Shigeru. "Design Datamining Based on Self-Organizing Map." Proceedings of the JSME annual meeting 2002.7 (2002): 23–24. http://dx.doi.org/10.1299/jsmemecjo.2002.7.0_23.

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32

Gritter, E. "De rechtmatigheid van datamining door de politie." Tijdschrift voor Bijzonder Strafrecht & Handhaving 4, no. 2 (2018): 113–15. http://dx.doi.org/10.5553/tbsenh/229567002018004002009.

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33

Aourag, H., F. Saidi, S. Broderick, and K. Rajan. "Designing Superlattices Ultra Hard Coatings: Datamining Approach." Journal of Computational and Theoretical Nanoscience 6, no. 4 (2009): 828–33. http://dx.doi.org/10.1166/jctn.2009.1114.

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34

Petkovich, J. C., A. Oliveira, Y. Zhang, T. Reidemeister, and S. Fischmeister. "DataMill: a distributed heterogeneous infrastructure forrobust experimentation." Software: Practice and Experience 46, no. 10 (2015): 1411–40. http://dx.doi.org/10.1002/spe.2382.

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35

D., Sudha, and Senthilkumar R. "A SHORT-LIVED LEARNING ON DATAMINING CONCEPTS." International Journal of Scientific Research and Modern Education 2, no. 1 (2017): 192–96. https://doi.org/10.5281/zenodo.822812.

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There is a huge amount of data available in the Information Industry. This data is of no use until it is converted into useful information. It is necessary to analyze this huge amount of data and extract useful information from it. Extraction of information is not the only process we need to perform; data mining also involves other processes such as Data Cleaning, Data Integration, Data Transformation, Data Mining, Pattern Evaluation and Data Presentation. Once all these processes are over, we would be able to use this information in many applications such as Fraud Detection, Market Analysis,

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36

Kuzmenko, O. V., V. V. Koibichuk, V. V. Yatsenko, and K. G. Hrytsenko. "Research of e-sports development world tendencies on the base of Data Mining methods." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 2 (2021): 117–24. http://dx.doi.org/10.17721/1812-5409.2021/2.16.

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The article analyzes the current state and trends of e-sports in the world by studying the time series of the number of requests from Internet users, obtained through the use of Google Trends. The positive and negative consequences of e-sports development in the world have been identified. The forecasting of world tendencies of e-sports by means of methods of data mining is carried out. Using the application of multivariate adaptive regression splines (MARSplines), a model of the relationship between the predictor - a time indicator and the dependent variable - the time series of the number of

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37

Gunia, Euis, Ade Irma Purnamasari, and Irfan Ali. "PENERAPAN DATAMINING DALAM MENENTUKAN POLA PENJUALAN PRODUK MENGGUNAKAN ALGORITMA FP-GROWTH." JATI (Jurnal Mahasiswa Teknik Informatika) 8, no. 2 (2024): 2417–22. http://dx.doi.org/10.36040/jati.v8i2.9506.

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Perkembangan bisnis di era digital menuntut penggunaan teknologi untuk meningkatkan efisiensi dan efektivitas operasional. Penelitian ini fokus pada penerapan datamining menggunakan algoritma FP-Growth dalam konteks penjualan produk di toko spesial juice dan sop buah. Tujuan penelitian ini yaitu untuk menerapkan datamining dengan algoritma FP-Growth guna menentukan pola penjualan produk yang relevan dan memberikan kontribusi signifikan terhadap keberhasilan toko spesial juice dan sop buah. Metode yang digunakan melalui pendekatan penelitian dengan mengumpulkan data penjualan historis dari toko

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38

Dekamin, Azam, and Ahmad Sheibatolhamdi. "A datamining approach for coronary artery disease prediction." Journal of Advanced Medical Sciences and Applied Technologies 3, no. 1 (2017): 29. http://dx.doi.org/10.18869/nrip.jamsat.3.1.29.

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39

Mary, S. Angel Latha, and K. R. Shankar Kumar. "Certain Investigation on Dynamic Clustering in Dynamic Datamining." International Journal of Data Mining Techniques and Applications 2, no. 2 (2013): 71–75. http://dx.doi.org/10.20894/ijdmta.102.002.002.008.

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40

Rezayi, Sorayya, Keivan Maghooli, and Soheila Saeedi. "Applying DataMining Approaches for Chronic Kidney Disease Diagnosis." International Journal of Intelligent Systems and Applications in Engineering 9, no. 4 (2021): 198–204. http://dx.doi.org/10.18201/ijisae.2021473640.

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41

Raorane, A. A., and R. V. Kulkarni. "APPLICATION OF DATAMINING TOOL TO CROP MANAGEMENT SYSTEM." Russian Journal of Agricultural and Socio-Economic Sciences 37, no. 1 (2015): 3–16. http://dx.doi.org/10.18551/rjoas.2015-01.01.

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42

J, ALBUNSKUBA, and SARAVANAKUMAR M. VENKATESH. "APPLICATION OF DATAMINING TECHNIQUES IN HIGHER EDUCATION SYSTEM." i-manager's Journal on Computer Science 4, no. 1 (2016): 8. http://dx.doi.org/10.26634/jcom.4.1.5987.

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43

Parkavi, A., Lakshmi K., and Srinivasa K.G. "Predicting effective course conduction strategy using Datamining techniques." Educational Research and Reviews 12, no. 24 (2017): 1188–98. http://dx.doi.org/10.5897/err2017.3266.

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44

hpa, Pus, and S. San thiya. "Review On Spyware - A Malware Detection Using Datamining." International Journal of Computer Trends and Technology 60, no. 3 (2018): 157–60. http://dx.doi.org/10.14445/22312803/ijctt-v60p124.

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45

Gray, Y' vonne D., Elizabeth D. Liddy, Dale Sanders, Henry Small, and Kathy Moeller Mls Ahip. "DataMining for healthcare professionals. Sponsored by SIG MED." Proceedings of the American Society for Information Science and Technology 39, no. 1 (2005): 464. http://dx.doi.org/10.1002/meet.1450390160.

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46

Kalai Selvi, T., S. Sasirekha, N. Deepika, V. Kanagalakshmi, and R. Kavya. "Customer Segmentation in IT Sector using Datamining Techniques." March 2024 6, no. 1 (2024): 15–26. http://dx.doi.org/10.36548/jaicn.2024.1.002.

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Due to its large client base, the IT industry generates enormous amounts of data every day. Business experts and decision-makers stressed that keeping current clients is less expensive than acquiring new ones. Business analysts and customer relationship management (CRM) analysts must understand the causes of customer attrition as well as the patterns of behavior found in the data of these clients. This research is a comprehensive study about churn prediction in IT industry it also suggests a churn prediction model to identify consumer churn and provide the reasons behind customer churn in the

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47

AISHWARYA.S, CHITRA.M, MRS.M.VIVEKA, and PRIYA NIVETHA. "APPROACHES OF DATAMINING IN NETWORK INTRUSION DETECTION SYSTEM." International Journal of Advances in Engineering & Scientific Research 1, no. 5 (2014): 129–34. https://doi.org/10.5281/zenodo.10725167.

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<strong><em>ABSTRACT</em></strong> <em>Network security technology has become crucial in protecting government and industry computing infrastructure. Due to the network attacks over the past few years the intrusion detection system (IDS) is increasingly becoming a crucial component to secure network. In recent years, data mining - based intrusion detection systems (IDSs) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behaviour in a changing environment. . Instrumenting components such as model deployment, data transformations, and cooperative distr

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48

Varsha, S., Kumar Aman, H.Ramya Shree C, and Payaswini. "Analysis of Datamining Algorithms for Diabetes Prediction Levels." Advanced Innovations in Computer Programming Languages 7, no. 1 (2025): 40–45. https://doi.org/10.5281/zenodo.14800441.

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<em>Diabetes an illness that can cause a worldwide wellbeing issue concurring to the universal diabetes league. By 2035 382 million individuals around the world will have diabetes and this number will twofold to 592 million. The body changes over nourishment into sugar or glucose and at this time our pancreas has to discharge affront which is critical for the release of glucose into cells sort 1 and 2. Diabetes are the foremost common maladies gestational diabetes and other maladies that happen amid pregnancy. Machine learning may be a modern wonder within the writing where machine learning le

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49

Ho, Wai-Chun George. "Three new species of genus Pylaemenes Stål (Phasmatodea: Heteropterygidae: Dataminae) from Vietnam." Zoological Systematics 43, no. 3 (2018): 276–82. https://doi.org/10.11865/zs.201826.

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Ho, Wai-Chun George (2018): Three new species of genus Pylaemenes Stål (Phasmatodea: Heteropterygidae: Dataminae) from Vietnam. Zoological Systematics 43 (3): 276-282, DOI: 10.11865/zs.201826, URL: http://zoobank.org/1eb06248-12d9-4fce-843a-de2e33024d67

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50

Joachim, Bresseel, and Constant Jérôme. "The Oriental stick insect genus Orestes Redtenbacher, 1906: Taxonomical notes and six new species from Vietnam (Phasmida: Heteropterygidae: Dataminae)." Belgian Journal of Entomology 58 (January 29, 2018): 1–62. https://doi.org/10.5281/zenodo.1162066.

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Joachim Bresseel, Jérôme Constant (2018): The Oriental stick insect genus Orestes Redtenbacher, 1906: Taxonomical notes and six new species from Vietnam (Phasmida: Heteropterygidae: Dataminae). Belgian Journal of Entomology 58: 1-62, ISBN: 2295-0214, DOI: 10.5281/zenodo.1162066

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