Research ArticleOpen accessIn the abstractA 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 abstractA Novel Distinguishability Based Weighted Feature Selection Algorithms for Improved Classification of Gene Microarray DatasetJ. Jeyachidra, M. PunithavalliData mining played vital role in comprehending, analyzing, understanding and interpreting microarray technology expression data. That includes search for genes that had similar or correlated patterns of expression. For that, the feature selection was one of the frequently used important techniques for data preprocessing. Many feature selection algorithms had been developed. Yet the persisting problem was in selecting optimal subset … …Journal of Computer Science, Vol. 11, Issue 2 · 2 Feb 2015 · 6,376 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractFROM DATA MINING AND KNOWLEDGE DISCOVERY TO BIG DATA ANALYTICS AND KNOWLEDGE EXTRACTION FOR APPLICATIONS IN SCIENCESubana Shanmuganathan"Data mining" for "knowledge discovery in databases" and associated computational operations first introduced in the mid-1990 s can no longer cope with the analytical issues relating to the so-called "big data". The recent buzzword big data refers to large volumes of diverse, dynamic, complex, longitudinal and/or distributed data generated from instruments, sensors, Internet transactions, email, video, click streams, noisy, structured/unstructured … …Journal of Computer Science, Vol. 10, Issue 12 · 20 Jan 2015 · 8,740 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 accessIn the abstractAN ALGORITHM FOR MINING USABLE RULES USING A HOLISTIC SWARM BASED APPROACHVeenu Mangat, Renu VigEvolutionary algorithms are capable of finding near optimal solutions to problems which are intractable to solve using conventional methods. One such problem is to accurately classify patients using rule mining methodology while controlling the size of output rules. A massive amount of data pertaining to medicine is generated and recorded daily. Uncovering useful knowledge and assisting decision makers in the … …Journal of Computer Science, Vol. 10, Issue 4 · 9 Dec 2013 · 6,667 accessesView PDFCite
Research ArticleOpen accessIn the abstractCombined 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 accessIn the abstractHybrid of Fuzzy Clustering Neural Network Over NSL Dataset for Intrusion Detection SystemDahlia Asyiqin Ahmad Zainaddin, Zurina Mohd HanapiIntrusion Detection System (IDS) is one of the component that take part in the system defence, to identify abnormal activities happening in the computer system. Nowadays, IDS facing composite demands to defeat modern attack activities from damaging the computer systems. Anomaly-Based IDS examines ongoing traffic, activity, transactions and behavior in order to identify intrusions by detecting anomalies. These technique identifies … …Journal of Computer Science, Vol. 9, Issue 3 · 4 May 2013 · 6,574 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient Prediction of Missing Itemset in Shopping CartV. Palanisamy, M. NirmalaMany researches has focused mainly on how to expedite the search for frequently co-occurring groups of items in "shopping cart" and less attention has been paid to the methods that exploit these "frequent itemsets" for prediction purposes. This study contributes to this task by proposing a technique that uses the partial information about the contents of a shopping cart for … …Journal of Computer Science, Vol. 9, Issue 1 · 8 Feb 2013 · 7,039 accessesView PDFCite
Research ArticleOpen accessIn the abstractSecured Disclosure of Sensitive Data in Data Mining TechniquesKirubhakar Gurusamy, Venkatesh ChakrapaniRecent advances in data collection, data dissemination and related technologies have inaugurated a new era of research where existing data mining algorithms should be reconsidered from the point of view of securing sensitive data. People have become increasingly unwilling to share their data. This frequently results in individuals either refusing to share their data or providing incorrect data. In turn, … …Journal of Computer Science, Vol. 8, Issue 12 · 18 Dec 2012 · 6,482 accessesView PDFCite