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  • CLASSIFICATION OF YOUTUBE COMMENT SPAM USING TF-IDF AND MULTINOMIAL NAÏVE BAYES CLASSIFIER 
    Oo, Nang Mya (University of Computer Studies, Yangon, 2022-06)
    Nowadays, social networking such as Facebook, YouTube, Telegram, Instagram, etc. are very popular among people as IT technologies are developing more and more. Facebook and YouTube are the most popular social media ...
  • Classification Process of Applicant’s data in a Job Agency using Rule-Based Classification Method 
    Lwin, Khine Pyae Sone; Than, May Lwin (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Nowadays, everybody has to work and so, they search the associated job balancing with their qualifications. For every graduated people have many opportunities in every workplace. But, they may not be free to search one job ...
  • Classification System Based On NBC For Cervical Cancer 
    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 ...
  • Classification the Stages of Breast Cancer Using ELEM2 (Extension of Learning from Examples Modules Version 2) Algorithm 
    Zin, Ei Ei (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    Breast cancer is the most common form of cancer among women world-wide and its early detection can improve the chances of successful treatment and recovery. In this paper we are using data mining techniques for diagnosis ...
  • 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 ...
  • Clause Level Reordering for Myanmar-English Translation System 
    Win, Aye Thida (Tenth International Conference On Computer Applications (ICCA 2012), 2012-02-28)
    Machine Translation (MT), one of the main problems to handle is word reordering. Myanmar Language and English language are linguistically different language pairs. Myanmar language is a verb final language and ...
  • 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, ...
  • Cloud Computing: Benefits and Limits on SPI model 
    Thwe, Khine Zar; Khaing, Phyu Phyu (Thirteenth International Conference On Computer Applications (ICCA 2015), 2015-02-05)
    Cloud computing is a term to deliver software, storage and processing. It increases system’s capability without changing the existing infrastructure, educating new people or taking license for the software. It improves ...
  • Cloud Data Center Resource Demand Prediction Model Development on Apache Spark 
    Than, Moh Moh; Thein, Thandar (Seventeenth International Conference on Computer Applications(ICCA 2019), 2019-02-27)
    Dynamic resource allocation in cloud data centers is a challenging problem. Resource prediction is a key feature for on-demand resource planning and efficient resource management of dynamic workload. This requires a ...
  • Cloud Deduplication based on Multiple Group Signature Scheme 
    Cho, Ei Mon; Koshiba, Takeshi (Fifteenth International Conference on Computer Applications(ICCA 2017), 2017-02-16)
    Increasing the volume of redundant data by multiple clients in cloud storage becomes a vital challenge. Multiple group setting schemes have recently become important for enabling deduplication for a cloud server. We ...
  • Cloud Infrastructure Resource Demand Prediction Model Using Parameter Optimization and Feature Selection 
    Myo, Myint Myat; Thein, Thandar (Tenth International Conference On Computer Applications (ICCA 2012), 2012-02-28)
    Cloud computing offer highly scalable, and economical infrastructure for promising heterogeneous platforms and various applications. According to the growing demand nature of cloud infrastructure resources, the cloud ...
  • Cloud Storage Forensics Framework 
    Aung, Nay Aung; Min, Myat Myat (Thirteenth International Conferences on Computer Applications(ICCA 2015), 2015-02-05)
    There are various types of cloud services with each type having a potentially different use in criminal activity. The storage as a service (StaaS) is showing significant growth as users adopt the capability to store data ...
  • 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 ...
  • Cluster-based Distributed File System on Private Cloud Data Center 
    Khaing, Cho Cho; Naing, Thinn Thu (Tenth International Conference On Computer Applications (ICCA 2012), 2012-02-28)
    The widespread popularity of Cloud computing as a preferred platform for the deployment of web applications has resulted in an enormous number of applications moving to the cloud, and the huge success of cloud ...
  • Cluster-Based Job Matching System 
    Sone, Phyo Pyae (University of Computer Studies, Yangon, 2020-01)
    A recruitment system comprises the processes, routines and elements essential to speedy and effective hiring for an organization or for a company. A good recruitment system includes all necessary features to aid management ...
  • Clustering Analogous Words in Myanmar Language using Word Embedding Model 
    Mon, Aye Myat; Soe, Khin Mar (Seventeenth International Conference on Computer Applications(ICCA 2019), 2019-02-27)
    Word embedding represents the words in terms of vectors. It is influenced on different NLP research areas such as document classification, author identification, sentiment analysis, etc. One of the most popular embedding ...
  • 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 ...

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