Proceedings ArticleDOI
Discovering similar time-series patterns with fuzzy clustering and DTW methods
Guoqing Chen,Qiang Wei,Hong Zhang +2 more
- Vol. 4, pp 2160-2164
TLDR
Fuzzy clustering and dynamic time warping methods are used to deal with fuzzy groupings of data attributes as well as with degrees of distance between time series patterned attributes, respectively.Abstract:
Data mining, as an active field, discovers useful knowledge from large data sets. This paper focuses on continuous time series data that have often been encountered in real applications (e.g., sales records, economic data and stock transactions) and discusses how to discover the hidden relationship among time series patterns in terms of their similarities. Fuzzy clustering and dynamic time warping (DTW) methods are used to deal with fuzzy groupings of data attributes as well as with degrees of distance between time series patterned attributes, respectively. An economic time series example is provided to help illustrate the ideas.read more
Citations
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Patent
Predictive and profile learning sales automation analytics system and method
TL;DR: In this paper, a sales automation system and method, namely a system and a method for scoring sales representative performance and forecasting future sales representatives performance, is presented, which can apply to a sales representative monitoring his own performance, comparing himself to others within the organization (or even between organizations using methods described in application).
Journal ArticleDOI
Clustering and symbolic analysis of cardiovascular signals: discovery and visualization of medically relevant patterns in long-term data using limited prior knowledge
TL;DR: Novel fully automated techniques for analyzing large amounts of cardiovascular data are described that incorporate no a priori knowledge about disease states, and are effective at identifying clinically relevant activity not only from symbolized ECG streams, but also from multimodal data obtained by symbolizing ECG and other physiological data streams.
Journal ArticleDOI
Mining time series data for segmentation by using Ant Colony Optimization
Sung-Shun Weng,Yuan-Hung Liu +1 more
TL;DR: The research result shows that time series segmentation run by the ACO algorithm not only automatically identifies the number of segments, but its segmentation cost was lower than that of the timeseries segmentation using the Bottom-Up method.
Overview of fuzzy associations mining
TL;DR: This paper focuses on associations of three kinds, namely, association rules, functional dependencies and pattern associations, and overviews major fuzzy logic extensions accordingly.
Journal ArticleDOI
Mixed data-driven decision-making in demand response management: An empirical evidence from dynamic time-warping based nonparametric-matching DID
TL;DR: Empirical results reveal that cash-incentive-based DR can effectively stimulate electricity-saving behaviour, and families from the treatment groups save an average of 27.3% of their total electricity consumption in the experimental period.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Proceedings ArticleDOI
Mining association rules between sets of items in large databases
TL;DR: An efficient algorithm is presented that generates all significant association rules between items in the database of customer transactions and incorporates buffer management and novel estimation and pruning techniques.
Proceedings ArticleDOI
Mining sequential patterns
TL;DR: Three algorithms are presented to solve the problem of mining sequential patterns over databases of customer transactions, and empirically evaluating their performance using synthetic data shows that two of them have comparable performance.
Proceedings Article
Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning
Usama M. Fayyad,Keki B. Irani +1 more
TL;DR: This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuous-valued attribute into multiple intervals.
Book ChapterDOI
Mining Sequential Patterns: Generalizations and Performance Improvements
TL;DR: This work adds time constraints that specify a minimum and/or maximum time period between adjacent elements in a pattern, and relax the restriction that the items in an element of a sequential pattern must come from the same transaction.