Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

245 results for “Data mining”
Set a search alert
Research ArticleOpen accessIn the abstractFuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision SupportS. Parkash Kumar, K. S. RamaswamiProblem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient … …Journal of Computer Science, Vol. 7, Issue 11 · 24 Aug 2011 · 6,677 accessesView PDFCite
Research ArticleOpen accessIn the abstractImpact of Bulldozer's Engine Load Factor on Fuel Consumption, CO2 Emission and CostVladislav Kecojevic, Dragan KomljenovicProblem statement: Bulldozers consume a large amount of diesel fuel and consequently produce a significant quantity of CO2. Environmental and economic cost issues related to fuel consumption and CO2 emission represent a substantial challenge to the mining industry. Approach: Impact of engine load conditions on fuel consumption and the subsequent CO2 emission and cost was analyzed for Caterpillar bulldozers. Results … …American Journal of Environmental Sciences, Vol. 7, Issue 2 · 26 May 2011 · 9,144 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving the Performance of Multivariate Bernoulli Model based Documents Clustering Algorithms using Transformation TechniquesPerumal Pitchandi, Nedunchezhian RajuProblem statement: Document clustering is the most important areas of data mining since they are very much and currently the subject of significant global research since such areas strengthen the enterprises of web intelligence, web mining, web search engine design and so forth. Generative models based on the multivariate Bernoulli and multinomial distributions have been widely used for text classification. … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,284 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 · 6,847 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Missing Attribute Values Using k-Means ClusteringNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Predicting the value for missing attributes is an important data preprocessing problem in data mining and knowledge discovery tasks. Several methods have been proposed to treat missing data and the one used more frequently is deleting instances containing at least one missing value of a feature. When the dataset has minimum number of missing attribute values then we … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,876 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Algorithm for Privacy Preserving Association Rule MiningIla Chandrakar, Yelipe Usha Rani, Mortha Manasa, Kondabala RenukaProblem statement: The objective of the hybrid algorithm for privacy preserving data mining is to hide certain sensitive information so that they cannot be discovered through association rule mining techniques. Approach: The sensitive items whether in Left Hand Side (LHS) or Right Hand Side (RHS) of the rule cannot be inferred through association rule mining algorithms by combining the concept … …Journal of Computer Science, Vol. 6, Issue 12 · 22 Nov 2010 · 7,339 accessesView PDFCite
Research ArticleOpen accessIn the abstractGlomalin Production and Microbial Activity in Soils Impacted by Gypsum Mining in a Brazilian Semiarid AreaAdalia Cavalcanti do Espírito Santo Mergulhao, Helio Almeida Burity, Fabio Sérgio Barbosa da Silva et al.Problem statement: Mining activities involve the removal of the vegetal cover and the soil organic layer, causing a severe environmental impact. In Northeast Brazil, 40% of the world’s crude gypsum is found in a semiarid area, making this region responsible for 95% of the gypsum demand in the national market. Although economically important, this activity is harmful to the environment. … …American Journal of Agricultural and Biological Sciences, Vol. 5, Issue 4 · 11 Nov 2010 · 9,028 accessesView PDFCite
Research ArticleOpen accessIn the abstractKnowledge Discovery in Biochemical Pathways Using MinepathwaysFord Lumban GaolProblem statement: The advancement of the biochemical research gives profound effect to the collection of biochemical data. Approach: In the recent years, data and networks in biochemical pathways are abundant that allow to do process mining in order to obtain useful information. By using graph theory as a tool to model these interactions, it can be formally find the solution. … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 7,057 accessesView PDFCite
Research ArticleOpen accessIn the abstractComputational Complexity between K-Means and K-Medoids Clustering Algorithms for Normal and Uniform Distributions of Data PointsT. Velmurugan, T. SanthanamProblem statement: Clustering is one of the most important research areas in the field of data mining. Clustering means creating groups of objects based on their features in such a way that the objects belonging to the same groups are similar and those belonging to different groups are dissimilar. Clustering is an unsupervised learning technique. The main advantage of clustering … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 19,451 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 · 7,031 accessesView PDFCite