Search Results - (( work detection mining algorithm ) OR ( java application testing algorithm ))
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Outlier Detection Technique in Data Mining: A Research Perspective
Published 2005“…Finding ,removing and detecting outliers is very important in data mining, for example error in large databases can be extremely common, so an important property of a data mining algorithm is robustness with respect to outliers in the database. …”
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Conference or Workshop Item -
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Effective mining on large databases for intrusion detection
Published 2014“…Data mining is a common automated way of generating normal patterns for intrusion detection systems. …”
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Potential norms detection in social agent societies
Published 2023“…In this paper, we propose a norms mining algorithm that detects a domain's potential norms, which we called the Potential Norms Mining Algorithm (PNMA). …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
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Thesis -
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Dissimilarity algorithm on conceptual graphs to mine text outliers
Published 2009“…In Comparison to other text outlier detection method, this approach managed to capture the semantics of documents through the use of CGs and is convenient to detect outliers through a simple dissimilarity function.Furthermore, our proposed algorithm retains a linear complexity with the increasing number of CGs.…”
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Obligation and Prohibition Norms Mining Algorithm for normative multi-agent systems
Published 2023“…In this paper, we present our proposed algorithm to detect the obligation and prohibition norms which we called the Obligation and Prohibition Norms Mining algorithm (OPNM). …”
Conference paper -
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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)
Published 2023“…The PNDT consists of five components: agent's belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent's belief base with new normative protocol. …”
Short Survey -
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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. …”
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Article -
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Designing a new model to detect Trojan Horse based on knowledge discovery and data mining
Published 2024thesis::master thesis -
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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Cancer Prediction Based On Data Mining Using Decision Tree Algorithm
Published 2022“…Many studies have been conducted in order to predict cancer. Different data mining method has showed up with its related algorithms were adopted by different research. …”
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Undergraduates Project Papers -
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023Conference Paper -
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Data Classification and Its Application in Credit Card Approval
Published 2004“…An analysis on the field of data mining is done to show how data mining, especially data classification, can help in businesses such as targeted marketing, credit card approval, fraud detection, medical diagnosis, and scientific work. …”
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Final Year Project -
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Journal -
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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