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12 results for “parallel mining”
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Research ArticleOpen accessPhrase in the titleModel 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
Research ArticleOpen accessIn the keywordsA Reformed K-Nearest Neighbors Algorithm for Big Data SetsVo Ngoc Phu, Vo Thi Ngoc TranA Data Mining Has Already Had Many Algorithms Which A K-Nearest Neighbors Algorithm, K-NN, Is A Famous Algorithm For Researchers. K-NN Is Very Effective On Small Data Sets, However It Takes A Lot Of Time To Run On Big Datasets. Today, Data Sets Often Have Millions Of Data Records, Hence, It Is Difficult To Implement K-NN On Big Data. In … …Journal of Computer Science, Vol. 14, Issue 9 · 8 Mar 2018 · 7,473 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMulti-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of WorkstationsS. Dehuri, A. K. Jagadev, A. Ghosh, R. MallThis study presents a fast and scalable multi-objective association rule mining technique using genetic algorithm from large database. The objective functions such as confidence factor, comprehensibility and interestingness can be thought of as different objectives of our association rule-mining problem and is treated as the basic input to the genetic algorithm. The outcomes of our algorithm are the set of … …American Journal of Applied Sciences, Vol. 3, Issue 11 · 30 Nov 2006 · 7,519 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA CURE Algorithm for Vietnamese Sentiment Classification in a Parallel EnvironmentVo Ngoc Phu, Vo Thi Ngoc Tran, Jack MaxSolutions to process big data are imperative and beneficial for numerous fields of research and commercial applications. Thus, a new model has been proposed in this paper to be used for big data set sentiment classification in the Cloudera parallel network environment. Clustering Using Representatives (CURE), combined with Hadoop MAP (M) / REDUCE (R) in Cloudera – a parallel network … …Journal of Computer Science, Vol. 15, Issue 10 · 19 Apr 2018 · 7,437 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA STING Algorithm and Multi-dimensional Vectors Used for English Sentiment Classification in a Distributed SystemVo Ngoc Phu, Vo Thi Ngoc TranSentiment classification is significant in everyday life, such as in political activities, commodity production and commercial activities. Finding a fast, highly accurate solution to classify emotion has been a challenge for scientists. In this research, we have proposed a new model for Big Data sentiment classification in the parallel network environment - a Cloudera system with Hadoop Map (M) and … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 1 · 22 Dec 2017 · 7,594 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIncremental DataGrid Mining Algorithm for Mobility Prediction of Mobile UsersU. Sakthi, R.S. BhuvaneswaranProblem statement: Mobility prediction is the important issue in Personal Communication Systems (PCS). Mobile users moving logs are stored in data grid located in different locations. Distributed data mining algorithm is applied on this moving logs to generate the mobility pattern of mobile users. As new moving logs are added to the data grid, existing mobility pattern becomes invalid and … …Journal of Computer Science, Vol. 5, Issue 2 · 28 Feb 2009 · 6,775 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Systematic Literature Review on Extraction of Parallel Corpora from Comparable CorporaDilshad Kaur, Satwinder SinghIn today’s Globalized Scenario, the requirement for translation is high and increasing rapidly in the number of fields, but it is difficult to translate everything manually. Machine Translation, which is dependent on corpora availability, is a medium for meeting this high demand for translation. Parallel corpora are used to gain most translation knowledge. But, the number and quality of parallel … …Journal of Computer Science, Vol. 17, Issue 10 · 27 Oct 2021 · 6,697 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnglish Sentiment Classification using Only the Sentiment Lexicons with a JOHNSON Coefficient in a Parallel Network EnvironmentVo Ngoc Phu, Vo Thi Ngoc TranSentiment classification is significant in everyday life, such as in political activities, commodity production and commercial activities. In this survey, we have proposed a new model for Big Data sentiment classification. We use many sentiment lexicons of our basis English Sentiment Dictionary (bESD) to classify 5,000,000 documents including 2,500,000 positive and 2,500,000 negative of our testing data set in English. … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 1 · 22 Dec 2017 · 7,327 accessesView PDFCite
Research ArticleOpen accessIn the abstractHighly Efficient Architecture for Scalable Focused Crawling Using Incremental Parallel Web CrawlerP. Jaganathan, T. KarthikeyanWith the growing industrial impact over the recent years in computer science, data mining has established itself as one of the most important disciplines. In the fast growing Web and in an appropriate amount of time, locating the resources that are precise and relevant is a huge challenge for the all-purpose single process crawlers, which makes the enhanced and the … …Journal of Computer Science, Vol. 11, Issue 1 · 13 Sep 2014 · 7,940 accessesView PDFCite
Research ArticleOpen accessIn the abstractMining Rare Itemset with Automated Support ThresholdsKanimozhi Selvi Chenniangirivalsu Sadhasivam, Tamilarasi AngamuthuProblem statement: Frequent itemset mining is an important task in data mining to discover the hidden, interesting associations between items in the database based on the user-specified support and confidence thresholds. Approach: In order to find important associations, an appropriate support threshold has to be specified. The support threshold plays a key role in deciding the interesting itemsets. The rare … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 6,844 accessesView PDFCite