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Research ArticleOpen accessPhrase in the titleA Comparison between Different Data Mining Algorithms in Freight Mode ChoiceAmir Samimi, Hesamoddin Razi-Ardakani, Amir NohekhanThis research aims to study application of support vector machine algorithm, artificial neural networks and five different types of decision trees in predicting mode choice of freight transportation. Performance of these models has been compared with log it model which is one the most prevalent statistical models in the field. Effect of factors such as cargo weight, distance, type and … …American Journal of Applied Sciences, Vol. 14, Issue 2 · 5 Feb 2017 · 7,623 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleWeb Structure Mining: Exploring Hyperlinks and Algorithms for Information RetrievalP. Ravi Kumar, Ashutosh Kumar SinghProblem statement: A study on hyperlink analysis and the algorithms used for link analysis in the Web Information retrieval was done. Approach: This research was initiated because of the dependability of search engines for information retrieval in the web. Understand the web structure mining and determine the importance of hyperlink in web information retrieval particularly using the Google Search engine. … …American Journal of Applied Sciences, Vol. 7, Issue 6 · 30 Jun 2010 · 9,055 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Algorithm for Privacy Preserving Association Rule MiningIla Chandrakar, Yelipe Usha Rani, Mortha Manasa, Kondabala RenukaProblem statement: The objective of the hybrid algorithm for privacy preserving data mining is to hide certain sensitive information so that they cannot be discovered through association rule mining techniques. Approach: The sensitive items whether in Left Hand Side (LHS) or Right Hand Side (RHS) of the rule cannot be inferred through association rule mining algorithms by combining the concept … …Journal of Computer Science, Vol. 6, Issue 12 · 22 Nov 2010 · 7,334 accessesView PDFCite
Research ArticleOpen accessIn the keywordsApplication of CART Algorithm in Blood Donors ClassificationT. Santhanam, Shyam SundaramProblem statement: This study used data mining modeling techniques to examine the blood donor classification. The availability of blood in blood banks is a critical and important aspect in a healthcare system. Blood banks (in the developing countries context) are typically based on a healthy person voluntarily donating blood and is used for transfusions or made into medications. The ability … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 8,624 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMining Level-Crossing Association Rules from Large DatabasesR. S. Thakur, R. C. Jain, K. R. PardasaniExisting algorithms for mining association rule at multiple concept level, restricted mining strong association among the concept at same level of a hierarchy. However mining level-crossing association rule at multiple concept level may lead to the discovery of mining strong association among at different level of hierarchy. In this study, a top-down progressive deepening method is developed for mining level-crossing … …Journal of Computer Science, Vol. 2, Issue 1 · 31 Jan 2006 · 7,312 accessesView PDFCite
Research ArticleOpen accessIn the keywordsClassifying and Predicting Students’ Performance using Improved Decision Tree C4.5 in Higher Education InstitutesMohammed Hikmat Sadiq, Nawzat Sadiq AhmedStudents’ information in higher education institutions increases yearly. It is hard for them to extract meaningful information from the huge amount of data manually. Such information can support academic staff to stop students from dropping out at the end of courses. This can be done by evaluating the students’ performance for the course and also by predicting their performance in … …Journal of Computer Science, Vol. 15, Issue 9 · 12 Sep 2019 · 9,168 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDocument Clustering Based on Firefly AlgorithmAthraa Jasim Mohammed, Yuhanis Yusof, Husniza HusniDocument clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters. Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization. This study explores the adaptation of another swarm algorithm which … …Journal of Computer Science, Vol. 11, Issue 3 · 26 Mar 2015 · 7,510 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
Literature ReviewOpen accessIn the abstractExtraction Performance of Essential Oils by Hydrodistillation Using Mathematical Models: A Systematic ReviewLenin Quiñones Huatangari, Frank Fernandez Rosillo, Eliana Milagros Cabrejos Barrios et al.Essential oils are complex mixtures of volatile organic compounds valued for their antimicrobial and antioxidant properties, with widespread applications in the food, pharmaceutical, and cosmetic industries. Among the various extraction techniques employed, hydrodistillation remains one of the most widely used methods. The extraction yield of essential oils by hydrodistillation is influenced by multiple factors, and quantifying these through mathematical modelling … …OnLine Journal of Biological Sciences, Vol. 26, Issue 1 · 25 Mar 2026 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite