Research ArticleOpen accessIn the abstractAn Efficient Algorithm for Mining Maximal Frequent Item SetsA. M.J.M.Z. Rahman, P. BalasubramanieProblem Statement: In today's life, the mining of frequent patterns is a basic problem in data mining applications. The algorithms which are used to generate these frequent patterns must perform efficiently. The objective was to propose an effective algorithm which generates frequent patterns in less time. Approach: We proposed an algorithm which was based on hashing technique and combines a … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractCustomized Privacy Preservation Using Unknowns to Stymie Unearthing Of Association RulesJ. Indumathi, G.V. UmaThe explosions of new data mining techniques has augmented privacy risks because now it is probable to powerfully coalesce and cross-examine massive data stores, accessible on the web, in the rummage around of earlier unidentified hidden patterns. Consecutively to make a overtly accessible system safe and sound, we must guarantee not only that private sensitive data have been trimmed out, … …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 7,117 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupport Measure Admissibility Based on Operations on Instance GraphsFord Lumban GaolThe concept of support is central to data mining. While the definition of support in transaction databases is intuitive and simple, that is not the case in graph datasets and databases. Most mining algorithms require the support of a pattern to be no grater than that of its subpatterns, a property called anti-monotonicity or admissibility. This study examines the requirements … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,825 accessesView PDFCite
Research ArticleOpen accessIn the abstractModel for Load Balancing On Processors in Parallel Mining of Frequent ItemsetsRavindra Patel, S. S. Rana, K. R. PardasaniThe existence of many large transactions distributed databases with high data schemas, the centralized approach for mining association rules in such databases will not be feasible. Some distributed algorithms have been developed [FDM, CD], but none of them have considered the problem of data skews in distributed mining of association rules. The skewness of datasets reduces the workload balancing between … …American Journal of Applied Sciences, Vol. 2, Issue 5 · 31 May 2005 · 7,341 accessesView PDFCite
Review ArticleOpen accessIn the abstractHealthcare Driven by Big Data AnalyticsCheryl Ann Alexander, Lidong WangText messages and social network posts are often included in big data and are frequently invaluable sources of health data. When machine learning or data mining is used, it is important to perform an automatic process for integrating all available and related health data. Artificial Neural Network (ANN) is one of the machine learning methods flexible in using algorithms to … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 3 · 28 Sep 2018 · 7,398 accessesView PDFCite
Research ArticleOpen accessIn the abstractCOMBINATION OF DIFFERENCE SUBSPACE AND OPPURTUNISTIC CLUSTERING ON HIGH DIMENSIONAL DATAM. Ravichandran, A. ShanmugamClustering is recognized as sigificant technique for analysing data and concentric effort has been taken in different domains comprises of recognition of pattern, statistical analysis and data mining for decades. Subspace clustering is developed from the group of cluster objects from all subspaces of a dataset. During clustering of objects involing higher dimension, the accuracy and effectiveness of traditional clustering … …Journal of Computer Science, Vol. 10, Issue 8 · 11 Mar 2014 · 6,355 accessesView PDFCite
Research ArticleOpen accessIn the abstractDISTINGUISHABILITY BASED WEIGHTED FEATURE SELECTION USING COLUMN WISE K NEIGHBORHOOD FOR THE CLASSIFICATION OF GENE MICROARRAY DATASETJeyachidra, PunithavalliIn data mining, much research is being carried out to discover the previously unknown, valid, novel, useful and understandable patterns in large databases. The patterns must be actionable so that they might be used for decision making to a variety of applications in healthcare. In this study, feature subset selection is an important area, where many approaches have been proposed. … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 13 Nov 2013 · 6,794 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Ant-Based Clustering Algorithm with Cluster Analysis TechniquesWafa’a Omar, Amr Badr, Abd El-Fattah HegazyCluster analysis is a data mining technology designed to derive a good understanding of data to solve clustering problems by extracting useful information from a large volume of mixed data elements. Recently, researchers have aimed to derive clustering algorithms from nature’s swarm behaviors. Ant-based clustering is an approach inspired by the natural clustering and sorting behavior of ant colonies. In … …Journal of Computer Science, Vol. 9, Issue 6 · 7 Jun 2013 · 7,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiscretization Numerical Data for Relational Data with One-to-Many RelationsRayner AlfredProblem statement: Handling numerical data stored in a relational database has been performed differently from handling those numerical data stored in a single table due to the multiple occurrences (one-to-many association) of an individual record in the non-target table and non-determinate relations between tables. Numbers in Multi-Relational Data Mining (MRDM) were often discretized, after considering the schema of the relational … …Journal of Computer Science, Vol. 5, Issue 7 · 31 Jul 2009 · 7,030 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Transformer Based Model to Detect Environmental Related Distress on Online Social MediaUtkarsh Sharma, Prateek Pandey, Shishir KumarOnline social media has been recently employed as the source of data for the detection of traffic-related activities and to control the flow of traffic in smart cities all over the world. Till now an ample amount of research work has been done in identification of traffic-related incidents with the help of online social media platforms (mostly Twitter). Along with … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 462 accessesView PDFCite