Data stream mining
Data Stream Mining – A Survey
... on data streams mainly motivated by many evolving applications which involve huge volumes of data generated from various domains, example, sensor data, data from supermarkets, telephone logs, ...
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IMPLEMENTATION OF ALGORITHM OUTPUT GRANULARITY APPROACH IN CLUSTERING ALGORITHM FOR MOBILE DATA STREAM MINING
... of data generated by mobile devices is of prime importance. Mobile data stream mining is a key technology for real-time analysis of data streams generated on-board the phone itself, for ...
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A Summarization Paradigm of Open Challenges for Data Stream Mining Issues
... of data that are continuously introduced and ...huge data sets and extracting valuable pattern from many real time applications are interesting factors in data mining ...the data ...
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Svm Classifier Algorithm for Data Stream Mining Using Hive and R
... of data, storing and retrieval of data is challenging factor. Data stream mining is the process of extracting knowledge structures from continuous, rapid data ...A data ...
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Data Stream Mining Big Data using Velocity Varying PSO Feature Selection
... of data is used to construct classification ...stationary data set, any update in it requires repeating of whole process ...dynamic stream processing, data streams are evolving and thus the ...
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Data stream mining techniques: a review
... using stream data mining ...Twitter’s stream that detects, clusters and tracks events using electric fields ...Twitter stream to detect real-time traffic events by using classification ...
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MOBILE DATA STREAM MINING: ADAPTATION STRATEGIES WITH AOG
... the mining algorithm output according to resource availability and data stream ...developed data stream mining algorithms for clustering classification frequent items and change ...
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Performance Evaluation and Estimation for Concept Drifting Data Stream Mining
... drifting data streams also requires some performance considerations as compared to classification tasks in static ...drifting data stream mining as the main requirement of online leaning is to ...
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Geometric Data Perturbation for Privacy Preserving in Data Stream Mining Mayur Prajapati 1Aniket Patel2
... helpful data from large ...of data stream are generated from completely different applications like shopping record, medical, network traffic ...Preserving Data Mining (PPDM) area unit ...
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Data stream mining: methods and challenges for handling concept drift.
... decision trees for data stream mining [21, 44, 63]. VFDTs are, however, only suitable for static streams and include no method for forgetting or restarting learning in the pres- ence of concept ...
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Modeling Dynamical Systems with Data Stream Mining
... on data streams almost to the letter (see ...using data stream mining ...individual data points arrive sequentially along the time dimension: The system identification (learning) algo- ...
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Data Stream Mining Developments and Applications
... diversified data each day. Such data can be processed to improve instantaneous decision making ...appropriate data from a large dataset, thereby using upcoming features to make a ...processing ...
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Concept Drift Detection in Data Stream Mining: The Review of Contemporary Literature
... - Mining process such as classification, clustering of progressive or dynamic data is a critical objective of the information retrieval and knowledge discovery; in particular, it is more sensitive in ...
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Data Mining & Data Stream Mining Open Source Tools
... of data mining was available in mid of ...of data. Here we describe open source tools for data mining and data stream ...for data stream mining today ...
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Geometric Data Perturbation Techniques in Privacy Preserving On Data Stream Mining
... -Data mining is the information technology that extracts valuable knowledge from large amounts of ...of data streams as a new type of data, data stream mining has recently ...
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AN ANALYTICAL FRAMEWORK FOR DATA STREAM MINING TECHNIQUES BASED ON CHALLENGES AND REQUIREMENTS
... Data stream can be conceived as a continuous and changing sequence of data that continuously arrive at a system to store or process ...generating data. The data are massive ...in ...
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Anomalous Network Packet Detection Using Data Stream Mining
... network data streams in real time. To re- solve this limitation, data stream mining techniques can be utilized to create a new type of IDS able to dy- namically model a stream of ...
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Principal Component Analysis Based Transformation for Privacy Preserving in Data Stream Mining
... Abstract— Data stream can be conceived as a continuous and changing sequence of data that continuously arrive at a system to store or ...of data streams include computer network traffic, phone ...
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Particle Swarm Optimization Feature Selection for Data Stream Mining
... Big data concept is used in every industry or any business. Big data can be characterized by 3Vs: the extreme volume of data, the wide variety of types of data and the velocity at which the ...
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Accelerated PSO Swarm Search Feature Selection with SVM for Data Stream Mining Big Data
... Big data technology has 3V challenges: Volume, Variety and Velocity. The datadelivery is continuous. Hence, processing needs to be real time and quickly responsive. Moreover, the memory requirement must be compact ...
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