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Now showing items 1651-1660 of 3438
Mining Interesting Subnetworks from Graphs with Node Attributes
(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 ...
Mapreduce-Enabled Scalable Nature-Inspired Approaches for Clustering
(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 ...
Object Classification Using Stacked Autoencoder and Convolutional Neural Network
(North Dakota State University, 2016)
In the recent years, deep learning has shown to have a formidable impact on object classification and has bolstered the advances in machine learning research. Many image datasets such as MNIST, CIFAR-10, SVHN, Imagenet, ...
Mining Representative Cohesive Dense Subgraphs
(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 ...
NDSU Scholar: Application to Search Articles Relevant to a Research Problem
(North Dakota State University, 2015)
Because of recent development in the field of computers, there has been substantial growth in the field of online education that varies from online tutors to electronic research papers. Now days, a student can find almost ...
Region Based Data Mining on Agriculture Data
(North Dakota State University, 2015)
Spatial Data Mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. Most relationships in spatial datasets are regional and there is a great ...
Market Basket Analysis Algorithm with MapReduce Using HDFS
(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 ...
Particle Swarm Optimization Algorithm: Variants and Comparisons
(North Dakota State University, 2015)
Since the introduction of Particle Swarm optimization by Dr. Eberhart and Dr. Kennedy, there have been many variations of the algorithm proposed by many researchers and various applications presented using the algorithm. ...
Does Domain Knowledge Increase Creativity During Requirements Development: An Empirical Investigation
(North Dakota State University, 2014)
To design and build a system/software, we need to understand the business of the organization, so understanding the business is very important for requirement analysis of such system. This requires an effective and efficient ...
Review Mining: Hierarchy Generation for Online Reviews
(North Dakota State University, 2015)
In the present world of ecommerce more and more products are purchased and sold online then via any other medium. With such massive drive in online shopping more and more information is being added every day on web regarding ...