6 articles for “datasets stored”

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Research ArticleOpen accessIn the keywordsBioDARA: Data Summarization Approach to Extracting Bio-Medical Structuring InformationChung Seng Kheau, Rayner Alfred, Joe Henry ObitProblem statement: Due to the ever growing amount of biomedical datasets stored in multiple tables, Information Extraction (IE) from these datasets is increasingly recognized as one of the crucial technologies in bioinformatics. However, for IE to be practically applicable, adaptability of a system is crucial, considering extremely diverse demands in biomedical IE application. One should be able to extract a … …Journal of Computer Science, Vol. 7, Issue 12 · 24 Oct 2011 · 7,936 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAnomaly Detection Algorithms for Streaming Data: Performance ComparisonZirije HasaniToday’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming … …Journal of Computer Science, Vol. 16, Issue 7 · 18 Jul 2020 · 7,288 accessesView PDF Cite

Research ArticleOpen accessIn the abstractComparative Study of Data Mining Classification Techniques for Detection and Prediction of Phishing WebsitesLuai Al-ShalabiData mining is the process of discovering or extracting information from large amount of data that are stored in databases or datasets such as phishing dataset. Phishing is a vital web security problem that involves simulating legitimate websites to mislead online users in order to steal their sensitive information. This paper aims to detect and predict the type of the … …Journal of Computer Science, Vol. 15, Issue 3 · 19 Mar 2019 · 7,473 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAdaptive Acceptance Criterion (AAC) Algorithm for Optimization ProblemsAnmar AbuhamdahOptimization methods commonly are designed for solving the optimization problems. Local search algorithms are optimization method, which are good candidate in exploiting the search space. However, most of them need parameter tuning and incapable of escaping from local optima. This work proposes non-parametric Acceptance Criterion (AC) that not relies on user-defined, which motivate to propose an Adaptive Acceptance Criterion (AAC). … …Journal of Computer Science, Vol. 11, Issue 4 · 23 Jul 2015 · 6,969 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA DATA WAREHOUSE DESIGN FOR THE DETECTION OF FRAUD IN THE SUPPLY CHAIN BY USING THE BENFORD’S LAWCornelia Kraus, Raul ValverdeLarge data volumes and the inability to analyse them enables fraudulent activities to go unnoticed in supply chain management processes such as procurement, warehouse management and inventory management. This fraud increases the cost of the supply chain management and a fraud detection mechanism is necessary to reduce the risk of fraud in this business area. This study was carried out … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 7 Jul 2014 · 8,740 accessesView PDF Cite

Research ArticleOpen accessIn the abstractSummarizing Relational Data Using Semi-Supervised Genetic Algorithm-Based Clustering TechniquesRayner AlfredProblem statement: In solving a classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets stored in multiple tables into a single table. Unfortunately, we may loss some information when we join tables with a high degree of one-to-many association. Therefore, data transformation becomes a tedious trial-and-error work and … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,585 accessesView PDF Cite