Mining data streams under block evolution
ACM SIGKDD Explorations Newsletter
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Maintaining variance and k-medians over data stream windows
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Better streaming algorithms for clustering problems
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Streaming-Data Algorithms for High-Quality Clustering
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Clustering binary data streams with K-means
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
What's hot and what's not: tracking most frequent items dynamically
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Clustering of time-series subsequences is meaningless: implications for previous and future research
Knowledge and Information Systems
ACM SIGMOD Record
Online Mining (Recently) Maximal Frequent Itemsets over Data Streams
RIDE '05 Proceedings of the 15th International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications
Processing High-Volume Stream Queries on a Supercomputer
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
STAGGER: Periodicity Mining of Data Streams Using Expanding Sliding Windows
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
An Efficient Classification System Based on Binary Search Trees for Data Streams Mining
ICONS '07 Proceedings of the Second International Conference on Systems
Online classification of nonstationary data streams
Intelligent Data Analysis
A Grid-Based Clustering Algorithm for Network Anomaly Detection
ISDPE '07 Proceedings of the The First International Symposium on Data, Privacy, and E-Commerce
Dynamic Incremental SVM learning Algorithm for Mining Data Streams
ISDPE '07 Proceedings of the The First International Symposium on Data, Privacy, and E-Commerce
An efficient algorithm for mining temporal high utility itemsets from data streams
Journal of Systems and Software
Tracking clusters in evolving data streams over sliding windows
Knowledge and Information Systems
Subspace Clustering of High Dimensional Data Streams
ICIS '08 Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008)
Hierarchical Clustering of Time-Series Data Streams
IEEE Transactions on Knowledge and Data Engineering
Info-fuzzy algorithms for mining dynamic data streams
Applied Soft Computing
E-Stream: Evolution-Based Technique for Stream Clustering
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
A Grid and Density-Based Clustering Algorithm for Processing Data Stream
WGEC '08 Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing
A Weighted Fuzzy Clustering Algorithm for Data Stream
CCCM '08 Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 01
Mining Closed Frequent Itemsets in Sliding Window over Data Streams
ICICIC '08 Proceedings of the 2008 3rd International Conference on Innovative Computing Information and Control
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 05
Efficient single-pass frequent pattern mining using a prefix-tree
Information Sciences: an International Journal
An Active Learning Method for Mining Time-Changing Data Streams
IITA '08 Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 02
An Improved Algorithm of Decision Trees for Streaming Data Based on VFDT
ISISE '08 Proceedings of the 2008 International Symposium on Information Science and Engieering - Volume 01
Mining of Frequent Itemsets from Streams of Uncertain Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
A Mining Maximal Frequent Itemsets over the Entire History of Data Streams
DBTA '09 Proceedings of the 2009 First International Workshop on Database Technology and Applications
Sliding window-based frequent pattern mining over data streams
Information Sciences: an International Journal
Mining Approximate Frequency Itemsets over Data Streams Based on D-Hash Table
SNPD '09 Proceedings of the 2009 10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing
Efficient Similarity Join over Multiple Stream Time Series
IEEE Transactions on Knowledge and Data Engineering
Efficient incremental mining of contrast patterns in changing data
Information Processing Letters
Density-Based Data Streams Clustering over Sliding Windows
FSKD '09 Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 05
Data stream forecasting for system fault prediction
Computers and Industrial Engineering
Mining association rules for the quality improvement of the production process
Expert Systems with Applications: An International Journal
Automatic bearing fault diagnosis based on one-class ν-SVM
Computers and Industrial Engineering
Computers and Industrial Engineering
A concept of web-based energy data quality assurance and control system
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
Systematic construction of anomaly detection benchmarks from real data
Proceedings of the ACM SIGKDD Workshop on Outlier Detection and Description
Graph-based reasoning in collaborative knowledge management for industrial maintenance
Computers in Industry
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Improving industrial product reliability, maintainability and thus availability is a challenging task for many industrial companies. In industry, there is a growing need to process data in real time, since the generated data volume exceeds the available storage capacity. This paper consists of a review of data stream mining and data stream management systems aimed at improving product availability. Further, a newly developed and validated grid-based classifier method is presented and compared to one-class support vector machine (OCSVM) and a polygon-based classifier. The results showed that, using 10% of the total data set to train the algorithm, all three methods achieved good (95% correct) overall classification accuracy. In addition, all three methods can be applied on both offline and online data. The speed of the resultant function from the OCSVM method was, not surprisingly, higher than the other two methods, but in industrial applications the OCSVMs' comparatively long time needed for training is a possible challenge. The main advantage of the grid-based classification method is that it allows for calculation of the probability (%) that a data point belongs to a specific class, and the method can be easily modified to be incremental. The high classification accuracy can be utilized to detect the failures at an early stage, thereby increasing the reliability and thus the availability of the product (since availability is a function of maintainability and reliability). In addition, the consequences of equipment failures in terms of time and cost can be mitigated.