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Journal articles on the topic 'Top-k class association rules'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Nguyen, Loan, Ngoc-Thanh Nguyen, and Bogdan Trawiński. "A Quick Method for Querying Top-k Rules from Class Association Rule Set." JUCS - Journal of Universal Computer Science 22, no. (6) (2016): 822–35. https://doi.org/10.3217/jucs-022-06-0822.

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Finding class association rules (CARs) is one of the most important research topics in data mining and knowledge discovery, with numerous applications in many fields. However, existing techniques usually generate an extremely large number of results, which makes analysis difficult. In many applications, experts are interested in only the most relevant results. Therefore, we propose a method for querying top-k CARs based on their supports. From the set of mined CARs that satisfy the minimum support and the minimum confidence thresholds, we use a QuickSort-based method to query top-k rules. The

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Juliet Thessalonica, D., H. Khanna Nehemiah, S. Sreejith, and A. Kannan. "Intelligent Mining of Association Rules Based on Nanopatterns for Code Smells Detection." Scientific Programming 2023 (April 13, 2023): 1–18. http://dx.doi.org/10.1155/2023/2973250.

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Software maintenance is an imperative step in software development. Code smells can arise as a result of poor design as well as frequent code changes due to changing needs. Early detection of code smells during software development can help with software maintenance. This work focuses on identifying code smells on Java software using nanopatterns. Nanopatterns are method-level code structures that reflect the presence of code smells. Nanopatterns are extracted using a command-line interface based on the ASM bytecode analysis. Class labels are extracted using three tools, namely inFusion, JDeod

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Mattiev, Jamolbek, Monte Davityan, and Branko Kavsek. "ACMKC: A Compact Associative Classification Model Using K-Modes Clustering with Rule Representations by Coverage." Mathematics 11, no. 18 (2023): 3978. http://dx.doi.org/10.3390/math11183978.

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The generation and analysis of vast amounts of data have become increasingly prevalent in diverse applications. In this study, we propose a novel approach to address the challenge of rule explosion in association rule mining by utilizing the coverage-based representations of clusters determined by K-modes. We utilize the FP-Growth algorithm to generate class association rules (CARs). To further enhance the interpretability and compactness of the rule set, we employ the K-modes clustering algorithm with a distance metric that binarizes the rules. The optimal number of clusters is determined usi

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Khafaga, Doaa Sami, Amal H. Alharbi, Israa Mohamed, and Khalid M. Hosny. "An Integrated Classification and Association Rule Technique for Early-Stage Diabetes Risk Prediction." Healthcare 10, no. 10 (2022): 2070. http://dx.doi.org/10.3390/healthcare10102070.

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The number of diabetic patients is increasing yearly worldwide, requiring the need for a quick intervention to help these people. Mortality rates are higher for diabetic patients with other serious health complications. Thus, early prediction for such diseases positively impacts healthcare quality and can prevent serious health complications later. This paper constructs an efficient prediction system for predicting diabetes in its early stage. The proposed system starts with a Local Outlier Factor (LOF)-based outlier detection technique to detect outlier data. A Balanced Bagging Classifier (BB

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Salah Gebril, Rami, and Hanan Mohammed Ali. "ANALYZING THE BREAST CANCER DATA IN BMC USING THE TECHNIQUES OF ASSOCIATION RULES AND LINEAR DISCRIMINANT." EPH - International Journal of Applied Science 2, no. 3 (2016): 28–37. http://dx.doi.org/10.53555/eijas.v2i3.139.

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Decision making in considered to be one of the main goals of Applied Statistical Analysis or Data Mining, especially in the field of medicine when decisions about criticalmedical procedures concerning patients are to be made regarding clinical diagnosis, surgical operations and treatments. In this study, a medical data related to breast cancer patients, are being analyzed using two statistical techniques. The data represent patients records in Benghazi Medical Center (BMC) admitted in the period (2003 – 2005). The data matrix consists of 16 variables corresponding to a total of 263 patients (c

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Yin, Rui, Xinrui Zhou, Jie Zheng, and Chee Keong Kwoh. "Computational identification of physicochemical signatures for host tropism of influenza A virus." Journal of Bioinformatics and Computational Biology 16, no. 06 (2018): 1840023. http://dx.doi.org/10.1142/s0219720018400231.

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Avian influenza viruses from migratory birds have managed to cross host species barriers and infected various hosts like human and swine. Epidemics and pandemics might occur when influenza viruses are adapted to humans, causing deaths and enormous economic loss. Receptor-binding specificity of the virus is one of the key factors for the transmission of influenza viruses across species. The determination of host tropism and understanding of molecular properties would help identify the mechanism why zoonotic influenza viruses can cross species barrier and infect humans. In this study, we have co

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Christopher U, EBELOGU, and AGU Edward O. "Clustering, Classification, and Association Rule Mining for Educational Datasets." International Journal of Advances in Scientific Research and Engineering 08, no. 10 (2022): 37–51. http://dx.doi.org/10.31695/ijasre.2022.8.10.4.

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Understanding students/pupils within the context of school is the focus of the expanding research topic known as educational data mining. Before the adoption of data mining tools in student analysis, it was challenging to identify students who were at risk of failure. However, using educational data mining tools has made it straightforward to examine student performance on previous exams. It helps teachers understand the kind of children they are working with. This knowledge can assist teachers to tailor their lecture notes to each student's needs and help difficult students focus more through

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Irawan, Herry, Eva Nurhazizah, and Joe Nathan C. G. Panjaitan. "Analisis Perpindahan Wisatawan dan Preferensi Desrinasi Wisata Favorit Berdasarkan Geotag Instagram (Studi Kasus pada Destinasi Wisata Bandung Raya)." Jurnal Teknologi Informasi dan Ilmu Komputer 9, no. 3 (2022): 639. http://dx.doi.org/10.25126/jtiik.2022935747.

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<p class="Judul2">Pariwisata adalah salah satu generator utama cadangan devisa nasional dengan pertumbuhan 10,1% per tahun. Pariwisata juga diharapkan akan menjadi kekuatan utama ekonomi lokal. Beberapa langkah ditempuh Pemerintah Provinsi Jawa Barat dalam rangka meningkatkan kunjungan wisata, salah satunya dengan penerapan teknologi komunikasi dan informasi atau dikenal dengan konsep <em>smart tourism</em>. Instagram adalah media yang memungkinkan pengguna dapat membagikan foto dan video. Data foto dan video pada Instagram di-<em>generate </em>oleh pengguna sendi

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Azizović, Melisa. "Big Data cluster analysis." Ekonomski izazovi 13, no. 25 (2024): 21–33. http://dx.doi.org/10.5937/ekoizazov2425020a.

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In this paper, we focused on cluster analysis as the most commonly used technique for grouping different objects. By clustering data, we can extract groups of similar objects from different collections. First, we defined Big Data and clustering to follow the rest of the paper. We presented the most popular techniques for clustering data, including partitioning, hierarchical clustering, density-based clustering, and network-based clustering. Big Data describes large amounts of data. High precision of big data can contribute to decision-making confidence, and better estimates can help increase e

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Lumactod, Flordeliza, and Lorenzo Capacio. "Effectiveness of Classroom Management Leadership Style and Teachers’ Performance." Psychology and Education: A Multidisciplinary Journal 35, no. 6 (2025): 667–75. https://doi.org/10.70838/pemj.350605.

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This study assessed the level of effectiveness of classroom management leadership style and teacher’s performance from 100 respondents of Malaybalay City Division, District IV, and V during the years 2022-2023. Since this study aims to determine the level of effectiveness of classroom management leadership style as perceived by the teachers in terms of class strategies, class activities, and STAR classroom, a descriptive-correlational design was used in this study. The teacher performance was found to have a substantial association with the success of the classroom management leadership style

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Rauf, Abdur, Muhammad Ammar, Mahnoor Azhar, Nasreen Noor, and Syeda Marriam Bakhtiar. "Unveiling the Secrets of Obesity with Machine Learning (ML) Techniques/Algorithms." Current Trends in OMICS 4, no. 1 (2024): 55–76. http://dx.doi.org/10.32350/cto.41.04.

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Obesity is the most significant health threat all over the world as it is considered the mother of all diseases. Recent decades have witnessed an extensive shift towards sedentary lifestyles including adaptation to luxury modes of transportation, processed food, lack of physical activities, and prolonged screen times. The trend of using cars and motorcycles to travel even short distances has emerged as a critical component in Pakistan's obesity pandemic. Whenever the causes of obesity are discussed, the focus remains always on processed food and genetic factors. This study is an effort to expl

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Shakhovskaya, N. B. Shakhovskaya, and N. I. Melnykova. "METHODS OF BUILDING A MODEL OF USER BEHAVIOR." Ukrainian Journal of Information Technology 2, no. 1 (2020): 43–51. http://dx.doi.org/10.23939/ujit2020.02.043.

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The number of clustering methods and algorithms were analysed and the peculiarities of their application were singled out. The main advantages of density based clustering methods are the ability to detect free-form clusters of different sizes and resistance to noise and emissions, and the disadvantages include high sensitivity to input parameters, poor class description and unsuitability for large data. The analysis showed that the main problem of all clustering algorithms is their scalability with increasing amount of processed data. The main problems of most of them are the difficulty of set

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Zhai, Yue, Xi Yu, and An Sheng Deng. "Class Association Rule Mining Based on Incremental Construction of Lattice." Applied Mechanics and Materials 571-572 (June 2014): 345–50. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.345.

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In the problem of mining classification rules, previous methods are too general or too over-fitting for a given dataset. In this paper, through analyzing the characteristics of concept lattice and indiscernible matrix, classification rule acquisition based on lattice was proposed. Our method includes two phase: (1) proposing incremental generating the nodes of lattice using indiscernible matrix. (2) Developing some theorems for pruning redundant rules quickly. It is shown by experimental results that our approach not only results in shorter execution times, but also avoids missing important ru

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Tang, Xiao Bin, and Yi Zhi Zhang. "Research on Topology Association Rules Algorithm Based on Spatial Constraints." Advanced Materials Research 998-999 (July 2014): 915–20. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.915.

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Spatial topological relation is an important and typical multilayer spatial relation, when Apriori is used to mining spatial constraint topology association rules, it will has some repeated computing. And so this paper proposes an algorithm of spatial constraint topology association rules mining based on complement set, which is used to mining spatial multilayer transverse association rules with constraint condition from spatial database. This algorithm generates candidate frequent topological itemsets with constraint condition not only by down-top search strategy as Apriori, but also by compu

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Wu, Lei, and Zhe Wang. "Research on Top-k Association Rules Mining Algorithm Based on Clustering." Journal of Physics: Conference Series 1682 (November 2020): 012064. http://dx.doi.org/10.1088/1742-6596/1682/1/012064.

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Karyawati, Eka, and Edi Winarko. "Class Association Rule Pada Metode Associative Classification." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 5, no. 3 (2011): 17. http://dx.doi.org/10.22146/ijccs.5207.

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Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining. Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list Intersection algorithm. This paper focuses on surveying and comparing the state of the art associative classification techniques with regards to the rule generation phase of associative classification algorithms. This phase includes frequent itemsets discovery and rules mining/extracting methods to generate the set of class association rules (CARs). Ther

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Xu, Yuzhao, Yanjing Sun, Zhanguo Ma, Hongjie Zhao, Yanfen Wang, and Nannan Lu. "Attribute Selection Based Genetic Network Programming for Intrusion Detection System." Journal of Advanced Computational Intelligence and Intelligent Informatics 26, no. 5 (2022): 671–83. http://dx.doi.org/10.20965/jaciii.2022.p0671.

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Intrusion detection, as a technology used to monitor abnormal behavior and maintain network security, has attracted many researchers’ attention in recent years. Thereinto, association rule mining is one of the mainstream methods to construct intrusion detection systems (IDS). However, the existing association rule algorithms face the challenges of high false positive rate and low detection rate. Meanwhile, too many rules might lead to the uncertainty increase that affects the performance of IDS. In order to tackle the above problems, a modified genetic network programming (GNP) is proposed for

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A., K. Shingarwade*1 &. Dr. P. N. Mulkalwar2. "DEVELOPMENT OF TOP K RULES FOR ASSOCIATION RULE MINING ON E-COMMERCE DATASET." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 2 (2019): 304–9. https://doi.org/10.5281/zenodo.2580039.

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Data mining an interdisciplinary research area spanning several disciplines such as machine learning, database system, expert system, intelligent information systems and statistic. Data mining has gradually became an active and important area of research because of previously unknown and interesting knowledge from very large real-world database. Many ideas of data mining have been investigated in several related fields. A unique but important aspect or idea of the problem lies in the significance of needs to extend their studies to include the nature of the contents of the real world database.

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Pal, Parashu Ram, Pankaj Pathak, and Shkurte Luma-Osmani. "IHAC: Incorporating Heuristics for Efficient Rule Generation & Rule Selection in Associative Classification." Journal of Information & Knowledge Management 20, no. 01 (2021): 2150010. http://dx.doi.org/10.1142/s0219649221500106.

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Associations rule mining along with classification rule mining are both significant techniques of mining of knowledge in the area of knowledge discovery in massive databases stored in different geographic locations of the world. Based on such combination of these two, class association rules for mining or associative classification methods have been generated, which, in far too many cases, showed higher prediction accuracy than platitudinous conventional classifiers. Motivated by the study, in this paper, we proposed a new approach, namely IHAC (Incorporating Heuristics for efficient rule gene

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Rehman, Z., and M. Shahbaz. "MINING TOP-K FREQUENT CLOSED ITEMSETS IN DATA STREAMS USING SLIDING WINDOW." Nucleus 50, no. 3 (2013): 229–40. https://doi.org/10.71330/thenucleus.2013.750.

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Frequent itemset mining has become a popular research area in data mining community since the last few years. There are two main technical hitches while finding frequent itemsets. First, to provide an appropriate minimum support value to start and user need to tune this minimum support value by running the algorithm again and again. Secondly, generated frequent itemsets are mostly numerous and as a result a number of association rules generated are also very large in numbers. Applications dealing with streaming environment need to process the data received at high rate, therefore, finding freq

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Thabtah, Fadi, Qazafi Mahmood, Lee McCluskey, and Hussein Abdel-Jaber. "A New Classification Based on Association Algorithm." Journal of Information & Knowledge Management 09, no. 01 (2010): 55–64. http://dx.doi.org/10.1142/s0219649210002486.

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Associative classification is a branch in data mining that employs association rule discovery methods in classification problems. In this paper, we introduce a novel data mining method called Looking at the Class (LC), which can be utilised in associative classification approach. Unlike known algorithms in associative classification such as Classification based on Association rule (CBA), which combine disjoint itemsets regardless of their class labels in the training phase, our method joins only itemsets with similar class labels. This saves too many unnecessary itemsets combining during the l

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Cao, Kai, and Yucong Duan. "Mining Top-k High Average-Utility Sequential Patterns for Resource Transformation." Applied Sciences 13, no. 22 (2023): 12340. http://dx.doi.org/10.3390/app132212340.

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High-utility sequential pattern mining (HUSPM) helps researchers find all subsequences that have high utility in a quantitative sequential database. The HUSPM approach appears to be well suited for resource transformation in DIKWP graphs. However, all the extensions of a high-utility sequential pattern (HUSP) also have a high utility that increases with its length. Therefore, it is difficult to obtain diverse patterns of resources. The patterns that consist of many low-utility items can also be a HUSP. In practice, such a long pattern is difficult to analyze. In addition, the low-utility items

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Zhu, Xiaolin. "Discovery of Traditional Chinese Medicine Prescription Patterns Containing Herbal Dosage Based on Multilevel Top-K Weighted Association Rules." Computational Intelligence and Neuroscience 2022 (May 25, 2022): 1–12. http://dx.doi.org/10.1155/2022/5466011.

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In traditional Chinese medicine (TCM), drug dosage is an important part of the prescription. Different doses of the same drug can have varying curative effects. Doctors must determine the drug combination and dosage in clinical practice based on the patient’s symptoms and treatment efficacy. Existing studies on the prescription pattern of TCM on the treatment of osteoporosis only analyze the frequency that a certain drug combination is used, without considering the treatment efficacy or drug dosage. As a result, we searched for and recorded existing literature on randomized controlled trials o

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Zhu, Xiaolin, Yongguo Liu, Qiaoqin Li, Yi Zhang, and Chuanbiao Wen. "Mining Effective Patterns of Chinese Medicinal Formulae Using Top-k Weighted Association Rules for the Internet of Medical Things." IEEE Access 6 (2018): 57840–55. http://dx.doi.org/10.1109/access.2018.2873677.

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Fan, Wenfei, Lihang Fan, Dandan Lin, and Min Xie. "Explaining GNN-Based Recommendations in Logic." Proceedings of the VLDB Endowment 18, no. 3 (2024): 715–28. https://doi.org/10.14778/3712221.3712237.

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This paper proposes Makex (MAKE senSE), a logic approach to explaining why a GNN-based model M ( x, y ) recommends item y to user x. It proposes a class of Rules for ExPlanations, denoted as REPs and defined with a graph pattern Q and dependency X → M ( x, y ), where X is a collection of predicates, and the model M ( x, y ) is treated as the consequence of the rule. Intuitively, given M ( x, y ), we discover pattern Q to identify relevant topology, and precondition X to disclose correlations, interactions and dependencies of vertex features; together they provide rationals behind prediction M

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Gao, Mengyang, Jun Wang, and Jing Yang. "Research into the Relationship between Personality and Behavior in Video Games, Based on Mining Association Rules." Mathematics 11, no. 3 (2023): 772. http://dx.doi.org/10.3390/math11030772.

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Nowadays, people have started to spend more and more time using the Internet, which has a crucial impact on people’s lives. Individual personality type is often the main factor dictating the various behaviors that people carry out, and it dominates their activities when socializing, communicating, and making choices in the virtual world. This study is dedicated to uncovering how the six dimensions of personality traits relate to players’ in-game behavior. This research is divided into two studies. Study 1 uses the K-means method to classify players in “Clash of Kings”, an online strategy video

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Zeman, Václav, Tomáš Kliegr, and Vojtěch Svátek. "RDFRules: Making RDF rule mining easier and even more efficient." Semantic Web 12, no. 4 (2021): 569–602. http://dx.doi.org/10.3233/sw-200413.

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AMIE+ is a state-of-the-art algorithm for learning rules from RDF knowledge graphs (KGs). Based on association rule learning, AMIE+ constituted a breakthrough in terms of speed on large data compared to the previous generation of ILP-based systems. In this paper we present several algorithmic extensions to AMIE+, which make it faster, and the support for data pre-processing and model post-processing, which provides a more comprehensive coverage of the linked data mining process than does the original AMIE+ implementation. The main contributions are related to performance improvement: (1) the t

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Paoin, W. "Lessons Learned from Data Mining of WHO Mortality Database." Methods of Information in Medicine 50, no. 04 (2011): 380–85. http://dx.doi.org/10.3414/me10-02-0019.

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SummaryObjectives: The objectives of this research were to test the ability of classification algorithms to predict the cause of death in the mortality data with unknown causes, to find association between common causes of death, to identify groups of countries based on their common causes of death, and to extract knowledge gained from data mining of the World Health Organization mortality database.Methods: The WEKA software version 3.5.3 was used for classification, clustering and association analysis of the World Health Organization mortality database which contained 1,109,537 records. Three

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Saleh, Mahjouba Ali, Sellappan Palaniappan, and Nasaraldeen Ali Alghazali Abdalla. "Predicting Student Performance using Data Mining Techniques in Libyan High Schools." Edukasi 15, no. 2 (2021): 91–100. http://dx.doi.org/10.15294/edukasi.v15i2.30068.

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Student performance in schools have been always the key factor for the teacher ability to teach and what brings good reputation to the school. Recently schools in Libya are facing an issue trying to figure out why students perform poorly in certain subjects and how can they know how they will perform next in the future in coming semesters in perspective subject. There are several methods proposed to predict the studentâ€™s performance, using data mining. This paper proposes using Math and English as key factors to predict the performance of the students. results and findings of the presented m

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Rahmati, Bahareh, and Mohammad Karim Sohrabi. "A Systematic Survey on High Utility Itemset Mining." International Journal of Information Technology & Decision Making 18, no. 04 (2019): 1113–85. http://dx.doi.org/10.1142/s0219622019300027.

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High utility itemset mining considers unit profits and quantities of items in a transaction database to extract more applicable and more useful association rules. Downward closure property, which causes significant pruning in frequent itemset mining, is not established in the utility of itemsets and so the mining problem will require alternative solutions to reduce its search space and to enhance its efficiency. Using an anti-monotonic upper bound of the utility function and exploiting efficient data structures for storing and compacting the dataset to perform efficient pruning strategies are

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Roslan, Nurshazneem, Saratha Sathasivam, and Farah Liyana Azizan. "Conditional random <i>k</i> satisfiability modeling for <i>k</i> = 1, 2 (CRAN2SAT) with non-monotonic Smish activation function in discrete Hopfield neural network." AIMS Mathematics 9, no. 2 (2024): 3911–56. http://dx.doi.org/10.3934/math.2024193.

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<abstract> <p>The current development of logic satisfiability in discrete Hopfield neural networks (DHNN)has been segregated into systematic logic and non-systematic logic. Most of the research tends to improve non-systematic logical rules to various extents, such as introducing the ratio of a negative literal and a flexible hybrid logical structure that combines systematic and non-systematic structures. However, the existing non-systematic logical rule exhibited a drawback concerning the impact of negative literal within the logical structure. Therefore, this paper presented a nov

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Lin, Rong-Ho, Wei-Wei Chuang, Chun-Ling Chuang, and Wan-Sin Chang. "Applied Big Data Analysis to Build Customer Product Recommendation Model." Sustainability 13, no. 9 (2021): 4985. http://dx.doi.org/10.3390/su13094985.

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With the development of the Internet environment, the trend of the retail industry in the future. It cannot be separated from the community, data and experience. Consumers’ lifestyles and purchasing behaviors are constantly changing and retailers must adopt policies to understand consumers. This research analyzes supermarkets most commonly touched by consumers in daily life. In order to find hidden information behind customer transaction data, it helps supermarkets to learn about the habits of customers to help them Formulate marketing strategies and improve the profitability of supermarkets a

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Awad, Nancy, Jean-Francois Couchot, Bechara Al Bouna, and Laurent Philippe. "Publishing Anonymized Set-Valued Data via Disassociation towards Analysis." Future Internet 12, no. 4 (2020): 71. http://dx.doi.org/10.3390/fi12040071.

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Data publishing is a challenging task for privacy preservation constraints. To ensure privacy, many anonymization techniques have been proposed. They differ in terms of the mathematical properties they verify and in terms of the functional objectives expected. Disassociation is one of the techniques that aim at anonymizing of set-valued datasets (e.g., discrete locations, search and shopping items) while guaranteeing the confidentiality property known as k m -anonymity. Disassociation separates the items of an itemset in vertical chunks to create ambiguity in the original associations. In a pr

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Nur Fitria, Tira, Wang Lita, Sun Limei, and Bevoor Bevoor. "Difficulties of Non-Arabic Study Program Students in Arabic Teaching and Learning Process at ITB AAS Indonesia." Journal International of Lingua and Technology 2, no. 1 (2023): 71–89. http://dx.doi.org/10.55849/jiltech.v2i1.383.

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This study investigates the difficulties of Non-Arabic study program students in Arabic learning at ITB AAS Indonesia. This research uses descriptive qualitative. This study involves 60 students of the Economy Sharia study program. The analysis shows internal and external factors of students’ difficulties in Arabic learning. The internal factors are 1) difficulty in writing Hijaiyah letters at the beginning of, in the middle, and at the end of the sentence. 2) difficulty in writing Hijaiyah letters in computer typing because it must have an Arabic Typesetting font. 3) belief that writing Arabi

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Lespessailles, Eric, and Toumi Hechmi. "Proton Pump Inhibitors and Bone Health: An Update Narrative Review." International Journal of Molecular Sciences 23, no. 18 (2022): 10733. http://dx.doi.org/10.3390/ijms231810733.

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Proton pump inhibitors (PPIs) are an antacid drug often used in acid-related disorders. They decrease acid secretion in the stomach by blocking an enzyme called H+/K+ ATPase which controls acid production. Introduced to the market in 1989, their use has increased rapidly worldwide and they are now among the top 10 most prescribed drugs in the United States. As of 2015, the FDA has already approved six drugs of this class (omeprazole, esomeprazole, lansoprazole, dexlansoprazole, pantoprazole and rabeprazole). Recently, the risks and benefits of long-term PPI use were questioned and many studies

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Sujatmiko, Ilham Nur, Imron Arifin, and Asep Sunandar. "Penguatan Pendidikan Karakter di SD." Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan 4, no. 8 (2019): 1113. http://dx.doi.org/10.17977/jptpp.v4i8.12684.

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<div align="center"><table width="645" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="439"><p class="Abstrak"><strong>Abstract:</strong> This study aims to (1) Describe the strategy and implementation of strengthening class-based character education at SD Muhammadiyah 08 Dau and MI Miftahul Ulum Sudimoro (2) Explain the strategy and implementation of strengthening culture-based character education at SD Muhammadiyah 08 Dau and MI Miftahul Ulum Sudimoro (3) Describe the supporting and inhibiting factors for the succe

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Gnerre, Sante, Jun Zhao, Adrian Bubie, et al. "Abstract 3128: Using Kmerizer, a germline and somatic genotyper for immune associated complex alleles in GuardantINFINITY, for immunotherapy response prediction using cfDNA." Cancer Research 83, no. 7_Supplement (2023): 3128. http://dx.doi.org/10.1158/1538-7445.am2023-3128.

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Abstract Background: HLA germline genotypes and somatic mutations show great promise as emerging biomarkers for immune checkpoint inhibitors (ICIs) and understanding patient prognosis. Multiple studies have shown that HLA homozygosity or loss-of-function somatic mutations negatively correlates ICI response rate. Here we present additional data on the algorithm Kmerizer, designed to perform HLA germline typing and somatic mutation detection from cfDNA input material, and we show how we use these in neoantigen prioritization for patient outcome prediction. Methods: Kmerizer first leverages the h

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Cai, Zhaoxiang, Zainab Noor, Adel T. Aref, et al. "Abstract 5391: Machine learning of cancer type and tissue of origin from proteomes of 1,277 human tissue samples and 975 cancer cell lines." Cancer Research 83, no. 7_Supplement (2023): 5391. http://dx.doi.org/10.1158/1538-7445.am2023-5391.

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Abstract Introduction Cancer type is determined through tumor morphology, aided by immunohistochemical staining. The development of machine learning (ML) models using histology slides has powered the image-based prediction of the site of origin in cancer of unknown primary (CUP). Here, we used ML on proteomic data to predict cancer types and tissue of origin from a sample cohort consisting of 1,277 human tissue samples spanning 44 cancer types. The training proteome datasets included two independent sets of proteomes acquired from a pan-cancer cell line collection and a subset of the tissue co

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Dr., K. Sravana Kumar. "MIDDLE CLASS MOVEMENTS." International Journal of Multidisciplinary Research and Modern Education 2, no. 2 (2016): 59–66. https://doi.org/10.5281/zenodo.61810.

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            The middle class is placed between labour and capital. It neither directly awns the means of production that pumps out the surplus generated by wage labour power, nor does it, by its own labour, produce the surplus which has use and exchange value. Broadly speaking, this class consists of the petty bourgeoisie and the white-collar workers. The former are either self-employed or involved in the distribution of commodities and the latter are non-manual office workers, supervisors and professionals. Thus, in terms of occupation, s

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Iacobucci, Ilaria, Marco Sazzini, Anna Ferrari, et al. "Susceptibility to Philadelphia-Positive acute Lymphoblastic Leukemia (ALL) Is Associated with a Germline Polymorphism In the ANRIL (CDKN2BAS) Locus." Blood 116, no. 21 (2010): 1670. http://dx.doi.org/10.1182/blood.v116.21.1670.1670.

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Abstract Abstract 1670 Among genes that are supposed to be involved in altered molecular pathways leading to leukemogenesis, the CDKN2A/B locus is particularly noteworthy since it encodes for the INK4-class cyclin dependent kinase inhibitors p15 INK4B, p16 INK4A and p14 ARF, which act as tumor suppressors. The CDKN2A/B locus has been found to be inactivated in several haeamatologic malignancies mainly due to deletion, aberrant repression or epigenetic silencing, whereas little is known about the potential role of its single nucleotide polymorphisms (SNPs) in leukemia susceptibility. To investi

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K., Sridevi. "The Art and Science of Entrepreneurial Leadership in Manufacturing Industries - A Case Study of Selected Manufacturing Units in Industrial Estate, Vijayawada." International Journal of Trend in Scientific Research and Development 3, no. 5 (2019): 2385–93. https://doi.org/10.5281/zenodo.3591505.

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The main objective of the empirical research is to identify and study, the styles of leadership in the manufacturing industrial sector in Industrial Estate, Vijayawada. The data was collected through case study method. Out of the 82 manufacturing units in the industrial estate, 50 are selected based on the line of activity and the type of industry, using judgement convenient sampling methods. 50 workers are contacted to assess the working conditions. The success levels of leadership style in terms of profit making employment generation and labour welfare are estimated. The schedule canvassed t

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Khaista Rahman and Muhammad Akram. "UNTOUCHABILITY AMONG MUSLIMS?" ĪQĀN 5, no. 1 (2022): 11–31. http://dx.doi.org/10.36755/iqan.v5i1.410.

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Islam is known for its egalitarian teachings and unequivocal rejection of discrimination based on color, race, and ethnicity. However, as is the case with many other religious traditions, the disparity between the teachings of Islam and the practice of different Muslim communities cannot be ruled out. In South Asia, the problem of untouchability is attributed to the Hindu caste system, with its roots in ancient Brahmanism. However, some scholars have opined that parallel social stratification exists among Muslim societies of the region, too, like labeling some ethnic Christians as Chuhra and c

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Taufikurrahman, Taufikurrahman, and Wahyu Hidayat. "Dinamika Politik Kelas Menengah Indonesia: Pergulatan Politik ICMI Membangun Demokrasi di Era Orde Baru." Panangkaran: Jurnal Penelitian Agama dan Masyarakat 3, no. 2 (2020): 149. http://dx.doi.org/10.14421/panangkaran.2019.0302-01.

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The political development of a country is determined by the system in force. Indonesia under a new order, for example, ruled by political system with authoritarian. In the new order era, the middle class Muslims did not gain flexibility in expressing their political participation as the impact of intervention and power domination. The changing in the political dynamics occurred in Indonesia in mid 1990s, one of which was characterized by the development of the Indonesian Muslim Scholars Association (ICMI). The emergence of ICMI is considered as the estuary of the long history struggle of the m

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Zwitscher-Maschine., Journal on Paul Klee /. Zeitschrift für internationale Klee-Studien. "Autorinnen und Autoren ZM17." Zwitscher-Maschine. Journal on Paul Klee / Zeitschrift für internationale Klee-Studien 17 (May 31, 2025): 82. https://doi.org/10.5281/zenodo.15564634.

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<strong>Rudolf Altrichter</strong> ist Philosoph und lebt als freier Schriftsteller in der Schweiz. Letzte Veröffentlichungen: <em>Spiegelungen. Traktat über die Liebe</em>, Oberhausen 2016; »Das Mysterium der Moderne. Über das Geheimnis als Betriebsgeheimnis der Kunst im Werk von Paul Klee«, in: <em>Zwitscher-Maschine</em>, Nr. 3, 2017; <em>Versuch über das Wirkliche</em>, Oberhausen 2018; <em>Über das Opfer</em>, Oberhausen 2019; <em>Metaphysisch denken</em>, Küsnacht 2020; <em>Betrachtungen</em>, Küsnacht 2021; <em>Über den Anlass</em>, Ne

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Baumgartner, Christina K., Marcia N. Paddock, Jennifer M. Frost, et al. "Abstract ND06: ABBV-CLS-484: An active site PTPN2/N1 inhibitor that augments the immune response and sensitizes tumors to immune-mediated killing." Cancer Research 82, no. 12_Supplement (2022): ND06. http://dx.doi.org/10.1158/1538-7445.am2022-nd06.

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Abstract Background: Pharmacologic inhibition of PTPN2 and PTPN1 (PTPN2/N1) represents a novel therapeutic approach in immuno-oncology that augments innate and adaptive immune responses in addition to enhancing tumor cell sensitivity to immune-mediated killing. PTPN2/N1 emerged as top hits in an in vivo CRISPR screen to identify tumor-intrinsic targets that enhance sensitivity and overcome resistance to anti-PD-1 treatment. PTPN2/N1 are phosphatases that act as negative regulators in numerous pathways including immune activation. While phosphatases have long been of interest, they are challeng

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ILOH, CONSTANCE. "Toward a New Model of College “choice” For a Twenty-first-century Context." Harvard Educational Review 88, no. 2 (2018): 227–44. http://dx.doi.org/10.17763/1943-5045-88.2.227.

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The past two decades have seen massive changes in the higher education landscape, including the heightened participation of post-traditional students, high reentry and mobility of students within and across sectors, and the increased visibility of open admissions institutions, such as community colleges and for-profit colleges. Despite these radical shifts, the most commonly used college choice frameworks still focus on the decisions of students who fit a stereotypical profile and are entering traditional institutions of higher learning for the first time. In this article, Constance Iloh argue

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Abel, John, Andreas Machl, Aslihan Gerhold-Ay, et al. "Abstract 6179: Machine learning (ML)-spatial quantification of the tumor microenvironment (TME) identifies differences associated with response to bintrafusp alfa (BA) vs pembrolizumab (PEM) treatment in the Phase 3 INTR@PID Lung 037 study." Cancer Research 84, no. 6_Supplement (2024): 6179. http://dx.doi.org/10.1158/1538-7445.am2024-6179.

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Abstract Background: ML digital pathology models can accurately quantify predictive biomarkers like PD-L1.1 We combined tissue conserving ML assessment of the TME in hematoxylin and eosin (H&E)-stained whole slide images (WSI) with RNAseq for high-dimensional TME quantification for biomarker discovery. The orthogonal methods were applied to a retrospective analysis of a Phase 3 trial directly comparing BA, a first-in-class bifunctional fusion protein composed of the extracellular domain of TGF-βRII (a TGF-β “trap”) fused to a human IgG1 monoclonal antibody blocking PD-L1, and the anti-PD-1

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Weisenthal, Samuel, Samuel J. Weisenthal, Caroline Quill, et al. "2416." Journal of Clinical and Translational Science 1, S1 (2017): 17–18. http://dx.doi.org/10.1017/cts.2017.75.

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OBJECTIVES/SPECIFIC AIMS: Our objective was to develop and evaluate a machine learning pipeline that uses electronic health record (EHR) data to predict acute kidney injury (AKI) during rehospitalization for patients who did not have an AKI episode in their most recent hospitalization. METHODS/STUDY POPULATION: The protocol under which this study falls was given exempt status by our institutional review board. The fully deidentified data set, containing all adult hospital admissions during a 2-year period, is a combination of administrative, laboratory, and pharmaceutical information. The admi

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Kumar, Rajiv. "Molecular Entities of Antimicrobial Drugsand Resistance Mechanism Underlying: Bioaccessibility, Bioavailability, and Bioaccumulation." International Journal of Bioorganic and Medicinal Chemistry 1, no. 1 (2021): 17–19. http://dx.doi.org/10.55124/bmc.v1i1.79.

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The three major groups of antifungal agents are there that are used in clinical use, azoles, polyenes, and allylamine/thiocarbamates, all own their antifungal activities to inhibit the reactivity of microbial or stop direct interaction of microbial with healthy cells.3 Microbial organometallic assimilation, the bioaccessibility, bioavailability, and bioaccumulation properties of inorganic metals in different antimicrobial moieties that are interrelated and classified as abiotic (e.g., organic carbon) and biotic (e.g., uptake and metabolism).4 IntroductionThe development of antifungal and

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Chowdhury, Uttam. "Regulation of transgelin and GST-pi proteins in the tissues of hamsters exposed to sodium arsenite." International Journal of Toxicology and Toxicity Assessment 1, no. 1 (2021): 1–8. http://dx.doi.org/10.55124/ijt.v1i1.49.

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Hamsters were exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days. Equal amounts of proteins from urinary bladder or liver extracts of control and arsenic-treated hamsters were labeled with Cy3 and Cy5 dyes, respectively. After differential in gel electrophoresis and analysis by the DeCyder software, several protein spots were found to be down-regulated and several were up regulated. Our experiments indicated that in the bladder tissues of hamsters exposed to arsenite, transgelin was down-regulated and GST-pi was up-regulated. The loss of transgelin expression has been report

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