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Browsing Local Conference on Parallel and Soft Computing by Title

Browsing Local Conference on Parallel and Soft Computing by Title

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  • Classification the Stages of Dental Caries Using C4.5 Decision Tree Algorithm 
    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 ...
  • Classifying Textual Documents Using Two Dimensional Probabilistic Model 
    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 ...
  • Classifying the Fields of Subjects Using Case-Based Reasoning 
    Wai, Hnin Yu; Than, Khin Aye (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Today text classification is a necessity due the very large amount of text documents that we have to deal with daily. Text classification is a task of assigning a text document into classes. In this thesis, the system will ...
  • Client-Server Application System Using RMI 
    Lay, Phyu Pyar Khin (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Most modern network programming is based on a client/server model. The Remote method Invocation API lets java objects on different hosts communicate with each other. A remote object lives on a server. In RMI application, ...
  • Cluster Based Data Storage Management System Using Hadoop Distributed File System 
    Kyaw, Myat (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Data storage is one of the important resources in cloud computing. There is a need to manage the data storage. This system is a cluster based data storage file system using Hadoop Distributed File System with the low cost ...
  • Clustering Analysis of Library System Using Divisive Method 
    Hlaing, Htwe Ei; Aung, Than Nwet (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Data mining is the automated or convenient extraction of patterns representing knowledge implicitly stored in large databases, data warehouses and other massive information repositories. Clustering has its roots in many ...
  • The Clustering Approach for Nutrient Foods 
    Myint, Swe Swe (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Clustering is the process of grouping the data into classes of similar objects. A cluster is a collection of data objects that are similar to one another within the same cluster and are dissimilar to the objects in other ...
  • Clustering Approach to Analyzing Student Data by using K-Means Algorithm 
    Wai, Khin Su Su; Min, Myat Myat (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Clustering is the process of grouping data into classes of clusters so that objects within a cluster have high similarity in comparison to one another, but are very dissimilar to objects in other clusters. K-means ...
  • Clustering Documents by Using Harmony K-means Algorithm 
    Win, Nwe War (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Clustering is currently one of the most crucial techniques for dealing with massive amount of heterogeneous information on the web, which is beyond human being’s capacity to digest. Recent studies have shown that the most ...
  • Clustering Homogeneous and Heterogeneous XML Documents by Summarizing Edge 
    Thu, May Myat; Tun, Khin Nwe Ni (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    Extensible Markup Language(XML) is a markup language that defines a set of rules for encoding documents in format that is both humanreliable and machine-reliable. Large amount of XML documents on the web require the ...
  • Clustering in Hyper-Linked Document Database using Efficient Graph Algorithm 
    Naing, Win Lai Lai; Htike, Thin Thin (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Clustering is an essential data mining task with numerous applications. Clustering is the process of grouping the data into classes or clusters, so that objects within a cluster have high similarity in comparison to one ...
  • Clustering of Web Usage Data Using Enhanced K-means Clustering Algorithm 
    Than, Hnin Yadana; Myint, May Tar Hla (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    Clustering is the process of partitioning or grouping a given set of patterns into disjoint clusters. Clustering web usage data requires developing specialized techniques based on the web log data. The methodology has ...
  • Clustering Patient Records using Fuzzy C-Means and Hard C-Means Algorithm 
    Soe, Theint Theint Nwe; Htwe, Tin Tin (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Data clustering is the process of dividing data elements into classes or clusters so that items in the same class are as similar as possible, and items in different classes are as dissimilar as possible. Most clustering ...
  • Clustering Spatial Data using DBSCAN (Density-Based Spatial Clustering of Applications with Noise) 
    Yan, Phyo Wai; Thida, Aye (Third Local Conference on Parallel and Soft Computing, 2009-08-03)
    Clustering algorithms are data attractive for the last class identification in spatial databases. This system presents the new clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise). ...
  • Clustering Technique using Concepts for Web Documents 
    Tar, Hmway Hmway; Nyunt, Thi Thi Soe (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Web document clustering becomes an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering techniques play core topics. One of the main issues for ...
  • Clustering the Navigation Pattern Using Graph Partitioning 
    Cho, Ei Mon; Soe, Khin Thanda (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    World Wide Web become as information gateway and as a medium for conducting business. People use web pages to retrieve information which may need or demand. Web mining can provide the navigation link to user by using ...
  • Clustering with Expectation Maximization in Web Usage Mining System 
    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 ...
  • Clustering XML Document Based On Path Similarities Using Structure Only 
    Mon, Ei Ei; Tun, Khin Nwe Ni (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    We propose a methodology for clustering XML documents on the basis of their structural similarities. This research combines the methods of common XPath and K-means clustering that improve the efficiency for those XML ...
  • Clustering XML Documents using Structural Similarity 
    Lwin, Moet Moet; Htoon, Ei Chaw (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Extensible Mark-up Language (XML) is increasingly important in data exchange and information management. The automatic processing and management of XML-based data are ever more popular research issues due to the ...
  • Collaborative Recommender System for Online Book Retailing by using Associative Rule Mining Approach 
    Phyo, Thet Mon; Oo, Nhinn Minn (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Recommender systems help the users to find and evaluate items of interest. They connect user with items to consume by associating the opinions of other individuals with the consuming user’s actions or opinions. Such system ...

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