Research ArticleOpen accessPhrase in the titleIs Single Scan based Restructuring Always a Suitable Approach to Handle Incremental Frequent Pattern Mining?Shafiul Alom Ahmed, Bhabesh NathIncremental mining of frequent patterns has attracted the attention of researchers in the last two decades. The researchers have explored the frequent pattern mining from incremental database problems by considering that the complete database to be processed can be accommodated in systems’ main memory even after the database gets updated very frequently. The FP-tree-based approaches were able to draw more … …Journal of Computer Science, Vol. 17, Issue 3 · 12 Mar 2021 · 6,923 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA 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 accessEvery word in the titleFREQUENT CORRELATED PERIODIC PATTERN MINING FOR LARGE VOLUME SET USING TIME SERIES DATAG. M. Karthik, S. KarthikFrequent pattern mining has been a widely used in the area of discovering association and correlations among real data sets. However, discovering interesting correlation relationship among huge number of co-occurrence patterns are complicated, a majority of them are superfluous or uninformative. Mining correlations among large pile of useless information is extraordinarily useful in real-time applications. In this study, we propose … …Journal of Computer Science, Vol. 10, Issue 10 · 30 Jun 2014 · 6,608 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMFTPM: Maximum Frequent Traversal Pattern Mining with Bidirectional ConstraintsJiadong Ren, Xiaojian Zhang, Huili PengAn important application of sequential mining technique is maximal frequent traversal pattern mining, since users' traversal pattern and motivation are latent in session sequence at some time segment. In this paper, a Frequent Traversal Pattern Tree structure with dwell time (FTP-Tree) is designed to store, compress the session database, and simplify the configuration of dwell time thresholds during mining. A … …Journal of Computer Science, Vol. 2, Issue 9 · 30 Sep 2006 · 6,530 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 keywordsMining Sequential Access Pattern with Low Support From Large Pre-Processed Web LogsS. Vijayalakshmi, V. MohanProblem statement: To find frequently occurring Sequential patterns from web log file on the basis of minimum support provided. We introduced an efficient strategy for discovering Web usage mining is the application of sequential pattern mining techniques to discover usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Approach: The approaches adopt … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 7,222 accessesView PDFCite
Research ArticleOpen accessIn the abstractVIRTUAL MINING MODEL FOR CLASSIFYING TEXT USING UNSUPERVISED LEARNINGS. Koteeswaran, E. Kannan, P. VisuIn real world data mining is emerging in various era, one of its most outstanding performance is held in various research such as Big data, multimedia mining, text mining etc. Each of the researcher proves their contribution with tremendous improvements in their proposal by means of mathematical representation. Empowering each problem with solutions are classified into mathematical and implementation models. … …American Journal of Applied Sciences, Vol. 11, Issue 5 · 20 Feb 2014 · 6,582 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordSupport 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