Faculty of Computer Science: Recent submissions

  • Dynamic Replication Management Scheme for Distributed File System 
    Thu, May Phyo; Nwe, Khine Moe; Aye, Kyar Nyo (1st International Conference on Big Data Analysis and Deep Learning Applications (ICBDL), 2018)
    Nowadays, replication technique is widely used in data center storage systems to prevent data loss. Data popularity is a key factor in data replication as popular files are accessed most frequently and then they ...
  • Dynamic Replication Management Scheme for Cloud Storage 
    Thu, May Phyo; Nwe, Khine Moe; Aye, Kyar Nyo (1st International Conference on Advanced Information Technologies (ICAIT), Yangon, 2017-11-01)
    Nowadays, replication technique is widely used in data center storage systems to prevent data loss. Data popularity is a key factor in data replication as popular files are accessed most frequently and then they ...
  • Security of Real-time Big Data Analytics Pipeline 
    Thein, Khin Me Me; Nyunt, Thi Thi Soe; Aye, Kyar Nyo (International Journal of Advances in Electronics and Computer Science (IJAECS), 2017-02)
    In today’s world, real-time data or streaming data can be conceived as a continuous and changing sequence of data that continuously arrive at a system to store or process. Big Data is also one of the hottest research ...
  • A Platform for Big Data Analytics on Distributed Scale-out Storage System 
    Aye, Kyar Nyo; Thein, Thandar (International Journal of Big Data Intelligence (IJBDI), 2015)
    Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Hadoop-based platform emerges to deal with big ...
  • Efficient Indexing and Searching Framework for Unstructured Data 
    Aye, Kyar Nyo; Thein, Ni Lar (International Conference on Software and Computing Technology (ICSCT), Singapore, 2011-12-10)
    The proliferation of unstructured data continues to grow within organizations of all types. This data growth has introduced the key question of how we effectively find and manage them in the growing sea of information. ...
  • Image Zooming with Linear Interpolation 
    Htwe, Ah Nge; Nge, Mi Mi (International Conference on e-Business (iNCEB), 2009-10)
    Image zooming is a vital role in image processing. The zoomed images can be distorted because of blocky or jaggy effects. Sometimes, there is a problem to define the content of image or photo. The distorted image is needed ...
  • Extraction of Frequent Patterns from Diabetes Cluster 
    Win, Myint Swe Lai; Phyu, Win Lei Lei (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Data mining is the process of discovering interesting knowledge, such as patterns, associations, changes, anomalies and significant structures, from large amounts of data stored in databases, data warehouses, or other ...
  • Comparative Study of Association Rules Mining 
    Aye, Thi Dar; Soe, Khin Mar (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Association rule mining is a technique to find useful patterns and associations in transactional databases. The mining of association rules can be mapped into the problem of discovering large (frequent) itemsets where ...
  • Building HMM-SGMM Continuous Automatic Speech Recognition on Myanmar Web News 
    Mon, Aye Nyein; Pa, Win Pa; Thu, Ye Kyaw (Fifteenth International Conference on Computer Applications (ICCA 2017), 2017-02-16)
    Myanmar language is a tonal and analytic language. It can be considered as an under-resourced language because of its linguistic resource availability. Therefore, speech data collection is a very challenging task in ...
  • Reordering Model with Recurrent Neural Networks for Myanmar- English Statistical Machine Translation 
    Nyein, May Kyi; Soe, Khin Mar (Fifteenth International Conference on Computer Applications (ICCA 2017), 2017-02-16)
    Word reordering is a problematic issue for language pairs with significantly different word orders, such as the translation between a subject-verb-object (SVO) language and a subject-object-verb (SOV) language. When ...
  • Exploring Features for Myanmar Named Entity Recognition 
    Mo, Hsu Myat; Nwet, Khin Thandar; Soe, Khin Mar (Fifteenth International Conference on Computer Applications(ICCA 2017), 2017-02-16)
    Named Entity Recognition (NER) is the task of classifying or labeling atomic elements in the text into predefined sets of named entity categories such as Person, Location, Organization or Number. NER is also a crucial ...
  • English-to-Myanmar Statistical Machine Translation Using a Language Model on Part-of-Speech in Decoding 
    Aye, Hnin Thu Zar; Ding, Chenchen; Pa, Win Pa; Nwet, Khin Thandar; Utiyama, Masao; Sumita, Eiichiro (Fifteenth International Conference on Computer Applications(ICCA 2017), 2017-02-16)
    In this study, we investigate English-to-Myanmar statistical machine translation (SMT) by using part-of-speech (POS) as linguistic inform-ation which is valuable for statistical machine translation systems to extract ...
  • Automatic Myanmar News Classification 
    Nwet, Khin Thandar; Khine, Aye Hnin; Soe, Khin Mar (Fifteenth International Conference on Computer Applications(ICCA 2017), 2017-02-16)
    Text classification is one of the major tasks of natural language processing and included in the interesting research areas of text data mining, which is about looking for patterns in natural language text. This ...
  • Applying Case-Based Reasoning Technology in Electronic Commerce Environment 
    San, Nyein Ei; Phyu, Win Lei Lei (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Case-based reasoning technology opens a very promising and enriching field for electronic commerce application, medical diagnosis, knowledge management, process control and so on. Case-based reasoning (CBR) is an ...
  • E-Learning System Development Using J2EE Framework Design Pattern 
    Win, Zin Sandar; Phyu, Sabai (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    In the context of software engineering, the design patterns are reusable solutions to common problems and are one of the key mechanisms for implementing reliable and maintainable software. Design patterns are fundamental ...
  • Automatic Mining of Verb Affixes for Myanmar Language with Unsupervised learning by using N-Grams 
    Than, Shalle Soe; Pa, Win Pa (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    A separable verb is a verb that is composed of a verb stem and a separable affix which is called verb affixes. Mining of verb affixes is to extract the various forms of verb affixes from any Myanmar sentences. A Method ...
  • Implementation of Word Alignment System for English- Myanmar Machine Translation 
    Khaing, Ei Ei; Soe, Khin Mar (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Statistical word alignment models have been widely used for various Natural Language Processing (NLP) problem. In statistical machine translation, word alignment models are trained on bilingual corpora. To build an SMT ...
  • Extracting Informative Content from Web Pages Using Content Extraction Algorithm 
    Hlaing, Yu Wai (Eleventh International Conference On Computer Applications (ICCA 2013), 2013-02-26)
    Apart from the main content blocks, almost all web pages on the Internet contain such blocks as navigation, copyright information, privacy notices, and advertisements, which are not related to the topic of the web page. ...
  • Attribute-Oriented Induction based Data Generalization for Relational Databases 
    Oo, Zin May; Phyu, Sabai (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Data Mining is the task of discovering interesting patterns from large amounts of data where the data can be stored in relational databases. Data generalization is a process that abstracts a large set of data in a ...
  • Genetic algorithm for Travelling Salesman Problem using MapReduce 
    Lwin, Hnin Thant (Eleventh International Conference On Computer Applications (ICCA 2013), 2013-02-26)
    The Travelling Salesman Problem (TSP) is one of the hardest and the most fundamental problems in Computer Science. Although several techniques have been used in the past to reduce the running time of TSP, Genetic algorithms ...

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