Browsing Computer Science by Title

Now showing items 220-239 of 405

    • Light Weight Health Application for Low End Cell Phones 

      Emamian, Peyman (North Dakota State University, 2016)
      Health applications are usually complicated and low end devices do not benefit from them. The focus of this thesis is on expandable health services platform for low end cell phones. Large number of mobile phones in the ...

    • A Linear Delay Algorithm for Enumerating All Connected Induced Subgraphs 

      Alokshiya, Mohammed (North Dakota State University, 2018)
      Real biological and social data is increasingly being represented as graphs. Pattern-mining-based graph learning and analysis techniques report meaningful biological subnetworks that elucidate important interactions among ...

    • A Linguistic Model for Improving Sentiment Analysis Systems 

      Hall, Jared Coleman (North Dakota State University, 2014)
      The value of automated sentiment analysis systems is increasing with the vast amount of consumer-generated content, allowing researchers to analyze the information readily available on the World Wide Web. Much research has ...

    • A Map Reduce Approach of K-Means++ Algorithm with Initial Equidistant Centers 

      Bhattacharyya, Krittika (North Dakota State University, 2015)
      Data clustering has been received considerable attention in many applications, such as data mining, document retrieval, image segmentation and pattern classification. The enlarging volumes of information emerging by the ...

    • Mapreduce-Enabled Scalable Nature-Inspired Approaches for Clustering 

      Aljarah, Ibrahim Mithgal (North Dakota State University, 2014)
      The increasing volume of data to be analyzed imposes new challenges to the data mining methodologies. Traditional data mining such as clustering methods do not scale well with larger data sizes and are computationally ...

    • Market Basket Analysis Algorithm with MapReduce Using HDFS 

      Nuthalapati, Aditya (North Dakota State University, 2017)
      Market basket analysis techniques are substantially important to every day’s business decision. The traditional single processor and main memory based computing approach is not capable of handling ever increasing large ...

    • Maximizing Sensor Coverage using Displacement to Remove Overlaps 

      Fazal, Kareemullah Khan (North Dakota State University, 2011)
      Sensor networks are wireless networks with small, low-cost sensors which collect and disseminate environmental data. They are used for monitoring and controlling physical environments from remote locations with better ...

    • Measurement of Non-Technical Skills of Software Development Teams 

      Bender, Lisa Louise (North Dakota State University, 2014)
      Software Development managers recognize that project team dynamics is a key component of the success of any project. Managers can have a project with well-defined goals, an adequate schedule, technically skilled people and ...

    • Metrics and Tools to Guide Design of Graphical User Interfaces 

      Alemerien, Khalid Ali (North Dakota State University, 2014)
      User interface design metrics assist developers evaluate interface designs in early phase before delivering the software to end users. This dissertation presents a metric-based tool called GUIEvaluator for evaluating the ...

    • Mining Approximate Frequent Dense Modules from Multiple Gene Expression Datasets 

      Seo, San Ha (North Dakota State University, 2021)
      Large amount of gene expression data has been collected for various environmental and biological conditions. Extracting dense modules that are recurrent in multiple gene coexpression networks has been shown to be promising ...

    • Mining Association Rules in Cloud 

      Roy, Pallavi (North Dakota State University, 2012)
      The association rule mining was implemented in Hadoop. An association rule mining helps in finding relation between the items or item sets in the given data. The performance of the algorithm was evaluated by testing it in ...

    • Mining Communities from Multi-Layered Graphs 

      Chao, Meng (North Dakota State University, 2013)
      Identifying communities from networks has been a subject of great interest in Biological and Social network analysis. Finding communities can help with tasks such as identifying and fighting disease. Using graphs to represent ...

    • Mining Connected Frequent Boolean Expressions 

      Kolte, Deepak (North Dakota State University, 2017)
      In this paper, we are finding Connected Frequent Boolean Expressions from cancer dataset [14] and protein protein interaction network [14] to discover group of dysregulated genes. Frequent Itemset Mining is a process of ...

    • Mining for Significant Information from Unstructured and Structured Biological Data and Its Applications 

      Al-Azzam, Omar Ghazi (North Dakota State University, 2012)
      Massive amounts of biological data are being accumulated in science. Searching for significant meaningful information and patterns from different types of data is necessary towards gaining knowledge from these large amounts ...

    • Mining Frequent Coherent Patterns from Weighted Graphs 

      Ahmed, Syed Kutub Uddin (North Dakota State University, 2014)
      Current research on network analysis; such as community detection, pattern mining and many other graph mining application mostly focus on large social or biological networks. Such experiments may find interesting patterns ...

    • Mining Interesting Subnetworks from Graphs with Node Attributes 

      Goparaju, Aditya Praneeth (North Dakota State University, 2018)
      A lot of complex data in many scientific domains such as social networks, computational biology and internet of things (IoT) is represented using graphs. With the global expansion of internet, social networks had an explosive ...

    • Mining Novel Knowledge from Biomedical Literature using Statistical Measures and Domain Knowledge 

      Jha, Kishlay (North Dakota State University, 2016)
      The problem of inferring novel knowledge from implicit facts by logically connecting independent fragments of literature is known as Literature Based Discovery (LBD). In LBD, to discover hidden links, it is important to ...

    • Mining Quasi-Frequent Subnetworks in Graph Networks Using Edge-Edge Summary Graph 

      Dawar, Priyanka (North Dakota State University, 2017)
      In today’s computing world, graphs have become increasingly important in modeling sophisticated structures, entities and their interactions, with broad applications including Bioinformatics, Computer Vision, Web analysis ...

    • Mining Representative Cohesive Dense Subgraphs 

      Brazier, Tyler (North Dakota State University, 2014)
      Data mining techniques have an important implication in social and biological network analysis, were we're interested in finding related complexes and communities. A modern paradigm for solving this problem involves finding ...

    • Mining Semantic Relationships Between Concepts Across Documents Using Wikipedia Knowledge 

      Yan, Peng (North Dakota State University, 2013)
      The ongoing astounding growth of text data has created an enormous need for fast and efficient Text Mining algorithms. However, the sparsity and high dimensionality of text data present great challenges for representing ...