Search Results - (( learning application server algorithm ) OR ( java implementation mining algorithm ))
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1
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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3
Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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4
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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6
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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7
Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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8
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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9
Implementing server-side federated learning in an edge-cloud framework for precision aquaculture
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10
On protecting data storage in mobile cloud computing paradigm
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11
Automatic email classification system / Phang Siew Ting
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12
Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…E-Learning is one of the Web based application where it will facing with large amount of data. …”
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13
Web usage mining for UUM learning care using association rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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14
Deep reinforcement learning online offloading for SWIPT multiple access edge computing network
Published 2021“…Deep Q network (DQN) is used to learn the binary offloading decisions from the learning experience. …”
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15
A resource-aware content adaptation approach for e-learning environment / Mohd Faisal Ibrahim
Published 2017“…Second, network aware applications architecture for E-Learning system was also proposed to dynamically adjust the users' demand based on network resources. …”
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16
Detection of SQL injection attack using machine learning
Published 2024“…Integrating this system into the backend of the web application server would augment the safety and security measures of the online application. …”
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17
Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm
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18
Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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19
Home intruder detection system using machine learning and IoT
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20
Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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