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26 articles for “association rule mining”
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Research ArticleOpen accessIn the keywordsA Descriptive Framework for the Multidimensional Medical Data Mining and RepresentationVeeramalai Sankaradass, Kannan ArputharajProblem statement: Association rule mining with fuzzy logic was explored by research for effective datamining and classification. Approach: It was used to find all the rules existing in the transactional database that satisfy some minimum support and minimum confidence constraints. Results: In this study, we propose new rule mining technique using fuzzy logic for mining medical data in order to … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 6,932 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBig Data Framework for Predicting Infectious Diseases to Improve Healthcare by Discovering New Symptom PatternsAmal Mohamed Mounir, Mohamed Ibrahim Marie, Laila Abd-ElhamidThe utilization of big data in infectious disease control represents a captivating opportunity, as these novel data streams offer the potential to enhance the timeliness of preventive measures. Various healthcare providers in both the public and private sectors generate, store, and analyse extensive datasets to enhance the quality of services they deliver. Recently, the outbreak of the new coronavirus, COVID-19, … …Journal of Computer Science, Vol. 20, Issue 10 · 2 Aug 2024 · 4,915 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImproving Question Answering System based on a Hybrid TechniqueAyatallah Gamal Abass, Sameh Abd El-Ghany, Ahmed Abo ElfetohQuestion Answering (QA) is a specialized form of information retrieval characterized by information needs that are expressed as natural language statements or questions. Query expansion is an approach which is used to extend question key words with new related words that are not included in question. In this study, anew association rule based question processing model is introduced. This model … …Journal of Computer Science, Vol. 14, Issue 9 · 15 Aug 2018 · 7,979 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA COMBINTORIAL TREE BASED FREQUENT PATTERN MININGN. Yamuna Devi, J. Devi ShreeFrequent pattern mining is a process of extracting frequently occurring itemset patterns from very large data storages. These frequent patterns are used to generate association rules which define the relationship among items. The strength of the relationship can be measured using two different units namely support value and confidence level. Any relationship that satisfies minimum threshold of support value is … …Journal of Computer Science, Vol. 10, Issue 9 · 23 Jun 2014 · 6,804 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPARTIAL RULE MATCH FOR FILTERING RULES IN ASSOCIATIVE CLASSIFICATIONYuhanis Yusof, Mohamed Hayel RefaiIn this study, we propose a new method to enhance the accuracy of Modified Multi-class Classification based on Association Rule (MMCAR) classifier. We introduce a Partial Rule Match Filtering (PRMF) method that allows a minimal match of the items in the rule’s body in order for the rule to be added into a classifier. Experiments on Reuters-21578 data sets are … …Journal of Computer Science, Vol. 10, Issue 4 · 9 Dec 2013 · 7,741 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUsing Unique-Prime-Factorization Theorem to Mine Frequent Patterns without Generating TreeHossein Tohidi, Hamidah IbrahimProblem statement: Ffrequent patterns are patterns that appear in a data set frequently. Finding such frequent patterns plays an essential role in mining associations, correlations and many other interesting relationships among data. Approach: Most of the previous studies adopt an Apriorilike approach. For huge database it may need to generate a huge number of candidate sets. An interest solution is … …American Journal of Economics and Business Administration, Vol. 3, Issue 1 · 7 Jan 2011 · 8,839 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 922 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Research ArticleOpen accessIn the abstractApriori-Based Analysis of Website PhishingRene Clint Gortifacion, Rhoderick Malangsa, Adelfa Diola, Tamar Mejia JuniorPhishing attacks put users' sensitive information at serious risk and are a rising concern in cybersecurity. In order to minimize the possible damage brought on by these assaults, it is essential to detect and categorize phishing websites correctly. In this study, we provide an Apriori-based analysis method for identifying and categorizing website phishing. The Apriori algorithm, which is frequently used … …Journal of Computer Science, Vol. 21, Issue 5 · 7 May 2025 · 5,040 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Survey of Anomaly Detection Using Data Mining Methods for Hypertext Transfer Protocol Web ServicesMohsen Kakavand, Norwati Mustapha, Aida Mustapha et al.In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Jan 2015 · 9,252 accessesView PDFCite