77 results for “mining algorithms”

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Research ArticleOpen accessAll words, across the recordImproving 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 · 7,281 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordImproving Term Extraction Using Particle Swarm Optimization TechniquesMohammad Syafrullah, Naomie SalimProblem statement: Term extraction is one of the layers in the ontology development process which has the task to extract all the terms contained in the input document automatically. The purpose of this process is to generate list of terms that are relevant to the domain of the input document. In the literature there are many approaches, techniques and algorithms … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 7,138 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordFast Algorithms for Outlier DetectionFawaz A.M. Masoud, Moh'd B. Al- Zoubi, Imad Salah, Ali Al-DahoudFinding fast algorithms to detect outliers (as unusual objects) by their distance to neighboring objects is a big desire. Two algorithms were proposed to detect outliers quickly. The first was based on the Partial Distance (PD) algorithm and the second was an improved version of the PD algorithm. It was found that the proposed algorithms reduced the number of distance … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,041 accessesView PDF Cite

Review ArticleOpen accessAll words, across the recordProcessing Skyline Queries in Incomplete Database: Issues, Challenges and Future TrendsYonis Gulzar, Ali A. Alwan, Norsaremah Salleh, Imad Fakhri Al ShaikhliIn many contemporary database applications such as multi-criteria decision-making and real-time decision-support applications, data mining, e-commerce and recommendation systems, users need query operators to process the data aiming at finding the results that best fit with their preferences. Skyline queries are one of the most predominant query operators that privileges to find the query results that return only those data … …Journal of Computer Science, Vol. 13, Issue 11 · 20 Nov 2017 · 8,002 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAdaptive Classification Method Based on Data DecompositionAyman E. Khedr, Amira M. Idrees, Ahmed I. El SeddawyKnowledge discovery is one of the vital fields which strongly supports decision making by applying different techniques based on the targeted field and the required information. Focusing on clustering and classification techniques, this paper presents an approach for adapting one of the classification algorithms for supporting decision making procedure in radiology data analysis field. The proposed adaptation is based on … …Journal of Computer Science, Vol. 12, Issue 1 · 20 Feb 2016 · 7,423 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordUsing Hyper Clustering Algorithms in Mobile Network PlanningLamiaa Fattouh Ibrahim, Hesham A. SalmanProblem statement: As a large amount of data stored in spatial databases, people may like to find groups of data which share similar features. Thus cluster analysis becomes an important area of research in data mining. Applications of clustering analysis have been utilized in many fields, such as when we search to construct a cluster served by base station in … …American Journal of Applied Sciences, Vol. 8, Issue 10 · 30 Aug 2011 · 7,504 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAnalysis of Resistance to Human Immunodeficiency Virus Protease Inhibitors Using Molecular Mechanics and Machine Learning StrategiesA. Harishchander, D. Alex Anand, Sanjib SenapatiProblem statement: Drug resistance is the most important factor, which influences the failure of current HIV therapies. So, the ability to predict the drug resistance of HIV-1 protease mutants will be useful in developing more effective and longer lasting treatment regimens. Approach: Drug resistance of HIV-1 protease is predicted with two current protease inhibitors (Indinavir and Saquinavir). The problem was … …Current Research in Medicine, Vol. 1, Issue 2 · 31 Oct 2010 · 7,204 accessesView PDF Cite