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38 results for “Pattern Mining”

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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 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 accessPhrase in the titleCombined Pattern Mining for D3M Using FuzzyS. S. Dhenakaran, S. MaheswariMany algorithms and models were developed but the findings are not actionable and lack of soft power while solving the complex problems. Domain Driven Data mining is used a major efforts to promote the action ability of the knowledge discovery in the real world smart decision making. Combined mining is one of the common methods for analyzing complex data for … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 1 Nov 2013 · 6,750 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 accessPhrase 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 accessEvery word in the titleMining 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 accessEvery word in the titleAn Interval Type-2 Fuzzy Association Rule Mining Approach to Pattern Discovery in Breast Cancer DatasetOlufunke Oladipupo, Oluwole Olajide, Stephen Adubi et al.In the literature, several methods explored to analyze breast cancer dataset have failed to sufficiently handle quantitative attribute sharp boundary problem to resolve inter and intra uncertainties in breast cancer dataset analysis. In this study an Interval Type-2 fuzzy association rule mining approach is proposed for pattern discovery in breast cancer dataset. In the first part of this analysis, the … …Journal of Computer Science, Vol. 17, Issue 3 · 6 Apr 2021 · 7,164 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Approach for User Navigation Pattern Discovery and Analysis for Web Usage MiningJ. Vellingiri, S. Kaliraj, S. Satheeshkumar, T. ParthibanWebsites on the internet are useful source of information in our day-to-day activity. Web Usage Mining (WUM) is one of the major applications of data mining, artificial intelligence and so on to the web data to predict the user's visiting behaviours and obtains their interests by analyzing the patterns. WUM has turned out to be one of the considerable areas … …Journal of Computer Science, Vol. 11, Issue 2 · 17 Sep 2014 · 7,630 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Approach for Discovering the Patterns by using PDBD Model in Big DataKamatchi Sundravadivelu, Muthuraman ThangarajBig data is a term that refers to information collected from a wide range of sources, including transaction processing systems, sensors, digital photographs, internet click stream logs, movies, and social media. The goal of text mining is to reveal new patterns and relationships that could lead to the discovery of previously unknown sources. It provides ample scope for interpretation of … …Journal of Computer Science, Vol. 18, Issue 5 · 21 May 2022 · 6,045 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFast Algorithms for Discovering Sequential Patterns in Massive DatasetsS. Dharani, Justus Rabi, Nanda Kumar, DarlyProblem statement: Sequential pattern mining is one of the specific data mining tasks, particularly from retail data. The task is to discover all sequential patterns with a user-specified minimum support, where support of a pattern is the number of data-sequences that contain the pattern. Approach: To find a sequence patterns variety of algorithm like AprioriAll and Generalized Sequential Patterns (GSP) … …Journal of Computer Science, Vol. 7, Issue 9 · 23 Jul 2011 · 7,280 accessesView PDFCite