UCSY's Research Repository: Recent submissions

  • Soe, Aye Thandar; Aye, Aye (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Frequent itemsets mining is a discovery of interesting associations and correlations between itemsets in transcational and relational databases. Associaton rule mining is a popular method in the retail sales industry where ...
  • Thein, Lwin Po Po; Nyunt, Kyi Zar (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    In data mining, association rule learning is a popular and well researched method for discovering interesting relations between variables in large databases. Association rules describe events that tend to occur together. ...
  • Htoo, Naw Lu Lu (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data mining has recently attracted tremendous amount ofattention in the database research because of its wide applicability in many areas, including decision support, market strategy and financial forecast. One of the most ...
  • Hlaing, Swe Swe (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Nowadays, the advancement in computing technology and the realibility of computers has led to signification changes in the way that data are collected and analyzed. This system is to predict the risk level of patients in ...
  • Soe, Mu Mu; Win, Thandar (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data Mining refers to using a variety of techniques to identify suggest of information or decision making knowledge in the database and extracting these in a way that they can put to use in areas such as decision support, ...
  • Wai, Tin Yu; Pa, Win Pa (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data mining is the process of analyzing data from different prespectives and summarizing it into useful information. Classification has been used for predicting medical diagnosis. Human experts in medical field are frequently ...
  • Naing, Soe Kalayar; Myo, Nyein Nyein (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Decision tree learning algorithm has been successfully using in data minng for training data set. In this system, the main task performed is using inductive methods to the given values of attributes of an unkown object to ...
  • Tun, Kaythi; Myo, Nyein Nyein (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Bayseian Classifier can predict class membership probabilities, such as the probability that a given sample belongs to a particular class. They are Powerful tools for solving classification problems in a vareity of domains. ...
  • Aye, Hnin Nwe; Pa, Win Pa (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Classification can be used as in the form of data analysis that can be used to extract models describing the important data classes. This aim of this paper is to exmaine the performance of decision tree algorithms. ...
  • Thu, Su Myat; Pa, Win Pa (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Classification of data objcts based on a predefined knowledge of the objects is a data mining and knowledge management techniques used grouping similar data objects together. It can be defined as supervised learning ...
  • Tun, Thinzar; Win, Chit Nilar (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data Mining aims to discover novel, interesting, and useful knowledge and patterns from databases. Classification is a data mining technique which addresses the problem of constructing a predication model for a ...
  • Than, Lei Mon; Tun, Zaw (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Web usage mining algorithms have been widely utilized for modeling user web navigation behaviour. This system introduces a model for mining of user’s navigation pattern. The model makes user model navigation pattern. The ...
  • Than, Wai Me Me; Kham, Nang Saing Moon (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    This paper presents the probabilistic model named Twodimensional Probabilistic Model (2DPM). In this model, terms are seen as disjoin events, and terms and categories are realeated to each other. Since the documents are ...
  • Mon, May Thet; Htwe, Tin Tin (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data mining is the process of analyzing data from different prespectives and summarizing it into useful information. Different applications often require the integration of application-specific methods. Classification is ...
  • Khaing, Yadanar; Min, Mar Mar (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    As the technology grows rapidly, many people take a great interest in computer. Many computerized systems are widely used in medical field such as making decisions for diagnosis to give treatment. Classification is a data ...
  • Thwin, Su Myat; Min, Mar Mar (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make valid predtictions. Classification is a form of data analysis that can be used ...
  • Phyo, Ohnmar; Aung, Moh Nyunt (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Today multimedia informatio has become an important component of our lives. Rapid increase in the amount of audio data demands for classify audio stream based on its content. This system will be developed audio classification ...
  • Lwin, No No Saw (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Clustering is the processof grouping the similar objects into the same group and produce characteristic for each cluster. Partition-based clustering algorithms are simple to implement. K-Means is one of the partition based ...
  • Hein, Pyae Sandi; Khine, May Aye (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Clustering (or cluster analysis) is one of the main data analysis techniques and deals with the organization of a set of objects in a multidimensional space into cohesive groups, called clusters. Each cluster contains ...
  • Mon, Aye Myat; Mar, Win (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data mining is the tasks of discovering interesting pattern from large amounts of data where the data can be stored in database, data warehouse. Data classification is the process of building a model from available data ...

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