Search Results - (( based application mining algorithm ) OR ( mobile applications learning algorithm ))
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…Mobile data stream mining (MDSM) applications in MECC systems involve massive heterogeneity at application and platform levels. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…In the online phase, the stream clustering algorithm for trajectories based on the lifespan of the cluster is proposed (CC_TRS) to overcome the limitations of the time window technique. …”
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An enhanced android botnet detection approach using feature refinement
Published 2019“…That adopts machine learning techniques to classify botware and benign applications. …”
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. …”
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GuitarApprentice: A Mobile Application for Acoustic Guitar Learning using Fast Fourier Transform algorithm
Published 2013“…The objective of the project is to create a learning-based mobile application for learning to play an acoustic guitar. …”
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
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Modifying iEclat algo ithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Moreover, this study introduces a mining algorithm called PC-miner to mine the mining model frequently with various values of minsup. …”
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A web usage mining approach based on LCS algorithm in online predicting recommendation systems
Published 2008“…To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. …”
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Clustering algorithm for market-basket analysis : the underlying concept of data mining technology
Published 2003“…This thesis seeks to understand the underlying concept of data mining technology in market-basket analysis. The clustering algorithm based on Small Large Ratios, SLR is presented in a manner that helps to understand the concept of data mining technology in marketbasket analysis. …”
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Algorithm visualization design guidelines for mobile leaning
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A new mobile botnet classification based on permission and API calls
Published 2024Subjects:Conference Paper -
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Review on ubiquitous education system with multi-agent synchronization on mobile learning application environment
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A Rough-Apriori Technique in Mining Linguistic Association Rules
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Book Chapter -
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Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…The enormous of information on the World Wide Web makes it obvious candidate for data mining research. Application of data mining techniques to the World Wide Web referred as Web mining where this term has been used in three distint ways; Web Content Mining, Web Structure Mining and Web Usage Mining. …”
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A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”
Proceedings Paper
