Faculty of Information Science Collection: Recent submissions

  • 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 ...
  • An Investigation into Variants of Great Deluge(GD) for Hyper-Heuristic (HH) Approach 
    Sin, Ei Shwe; Kham, Nang Saing Moon (Sixth Local Conference on Parallel and Soft Computing, 2011-12-29)
    Today, Hyper-Heuristic is not new in AI Field. It is an emerged search technology to select or generate (new) low level heuristics for combinatorial optimization problem and has been applied in many problem domains: personal ...
  • FAQ Finder for Computer Related Questions 
    Oo, Lwin Mar; Kham, Nang Saing Moon (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    This paper presents Frequently Asked Question (FAQ) finder system that uses a natural language question based on interface to access text information sources specifically text files organized as question-answer pairs ...
  • Decision Support System using Analytic Hierarchy Process(AHP) on Multiagent System 
    Oo, Myat Noe; Kham, Nang Saing Moon (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Electronic commerce (e-commerce) has changed the outlook of traditional business trading behavior. E-commerce includes different types of activities related to the online sales of goods and services. In this paper, ...
  • Machine Learning Based Android Malware Detection using Significant Permission Identification 
    Kyaw, May Thu; Kham, Nang Saing Moon (Seventeenth International Conference on Computer Applications(ICCA 2019), 2019-02-27)
    The increasing popularity of smartphones and tablets has introduced Android malware which is rapidly becoming a potential threat to users. A recent report indicates the alarming growth rate of Android malware in which ...
  • Intelligence Routing Plan using K-d tree and Smart-A* with Google Map Data 
    Soe, Nyein Chan; Thein, Thin Lai Lai (Seventeenth International Conference on Computer Applications(ICCA 2019), 2019-02-27)
    Road traffic congestion or jam is main problem in urban area of both developing and developed countries. In order to solve this problem, traffic congestion states of road networks are estimated so that congested road ...
  • Real-Time Human Motion Detection and Tracking with Learning based Representation 
    Win, Sandar; Thein, Thin Lai Lai (Seventeenth International Conference on Computer Applications(ICCA 2019), 2019-02-27)
    Nowadays, real-time information is very important and learning based human motion has fascinated range from detection to tracking state in Computer Vision. In this system, the real-time videos are used to detect, track, ...
  • Trust Prediction Framework for Social Networking 
    Sint, Hla Sann; Oo, Khine Khine (Seventeenth International Conference on Computer Applications(ICCA 2019), 2019-02-27)
    In today's hyper-connected society, understanding the mechanisms of trust is crucial. Trust issues are critical to solving problems. Trust phenomenon has been extensively explored by a variety of disciplines across the ...
  • Application of RFID based Student Attendance System using Cloud Storage and IOT 
    Mon, Soe Soe; Kham, Nang Saing Moon; Aung, Than Htike (Seventeenth International Conference on Computer Applications(ICCA 2019), 2019-02-27)
    In current years, there have been development of the number of intelligent tools based Radio Frequency Identification (RFID). RFID systems have been used successfully working to many areas such as transport, health ...
  • Ontology based Recommender System using Content-based Filtering and AHP methods 
    Mon, Shun Ei; Kham, Nang Saing Moon (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    Recommender systems on web pages are a subclass of information filtering system that seeks the relevant web pages according to prediction of the 'rating' or 'preference' that a user would give web page. Nowadays, the ...
  • Web Usage Mining Using Clustering and Association Rule Mining 
    Thwin, Aye Theingi; Kham, Nang Saing Moon (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    Data mining methods are used to discover the behaviour of the users. Therefore, the data used for the mining purpose must be qualified for the data cleaning stage and must be considered and planned efficiently to meet ...
  • Shortcut Links Suggestion by Web Usage Mining 
    Hlaing, Ei Mon; Kham, Nang Saing Moon (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    Today’s websites are having a lot of small parts or details arranged in a complicated way and are therefore sometimes difficult to understand for the visitors.The web sites designers are faced with increasing ...
  • Location Based Service and Contextual Preference Aware (LBSCPA) System on Mobile Platform 
    Thu, Yin Yin; Kham, Nang Saing Moon (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    The explosive growth of location-detection devices, wireless communications, and mobile internet has resulted in the realization of locationbased services as commercial products and research prototypes. Unfortunately, ...
  • Enhancing Neural Network Training by Using Artificial Bee Colony Algorithm 
    Thuzar, Pyae Phyo; Kham, Nang Saing Moon (2017-12-27)
    Multilayer feedforward networks are one of the most used neural networks in various domains because of their universal approximation ability. One of the popular algorithms for training multilayer feedforward network ...
  • Comparison of Differential Evolution and Back-propagation Algorithms at Training Neural Network 
    Mon, Cho Thel; Thein, Thin Lai Lai (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    In data mining, multilayer feed-forward networks are one of the most used neural networks in various domains because of their universal approximation capability. Back-propagation (BP) uses two phases, feed-forward and ...
  • Implementing Dynamic Traffic Route Guidance System applying Graph Database 
    Kham, Nang Saing Moon; Maw, Sis Hmue (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    All around the world, people experience delays due to bad traffic conditions and finding the best possible roads in road network from given source to given target location is an everyday problem. Graph database technology ...
  • Mandatory Access Control ByBiba Model 
    Zune, Sheilar; Kham, Nang Saing Moon (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    Database security and integrity are essential aspects of an organization’s security posture. Database security is the system, processes, and procedures that protect a database from unintended activities. It is important ...
  • Rule-based Consciousness Expert System by Abhidhamma model with Forward Chaining Technique 
    Htay, Hsu Myat; Oo, Khine Khine (Eighth Local Conference on Parallel and Soft Computing, 2017-12-27)
    The Abhidhamma is one of the three parts of the Pali cannon, the Tipitaka, the main texts of Theravada Buddhism and is sometimes described as ‘Buddhist Psychology’ [2]. Human mind is consciousness (citta) and mental ...
  • Searching Suitable Employee for the Work by Using Partitioning Methods 
    Nwe, Win Hay Mar; Kham, Nang Saing Moon (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Conventional database query methods are inadequate to extract useful information from huge data banks. Cluster analysis is one of the major data analysis methods, and process of grouping a set of physical or abstract ...
  • A Comparative Study on Transaction Database Mining Algorithms 
    Soe, Hay Mar; Kham, Nang Saing Moon (Fifth Local Conference on Parallel and Soft Computing, 2010-12-16)
    Association Rules is the process of identifying relationships among set of items in transaction database. Finding frequent itemsets is the most expensive step in Association rule discovery. Real world datasets are ...

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