Journal Article10.1002/WIDM.27
Contrast and change mining
40
TL;DR: This article provides an overview of recent works on methods for change analysis, thereby focusing on contrast mining and change mining, the two emerging subfields of contemporary data mining research.
read more
Abstract: Because the world with its markets, innovations, and customers is changing faster than ever before, the key to survival for businesses is the ability to detect, assess, and respond to changing conditions timely and intelligently. Understanding changes and reacting to or acting upon them therefore become a strategic issue not only for companies but also in many other domains. The corresponding need for knowledge has been answered by data mining research by proposing a multitude of methods for analyzing different aspects of change. This article provides an overview of recent works on methods for change analysis, thereby focusing on contrast mining and change mining, the two emerging subfields of contemporary data mining research. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 215–230 DOI: 10.1002/widm.27
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
The Analysis of Time Series: An Introduction
TL;DR: The analysis of time series: An Introduction, 4th edn. as discussed by the authors by C. Chatfield, C. Chapman and Hall, London, 1989. ISBN 0 412 31820 2.
1.7K
A survey of methods for time series change point detection
TL;DR: This survey article enumerates, categorizes, and compares many of the methods that have been proposed to detect change points in time series, and presents some grand challenges for the community to consider.
1.1K
•Journal Article
Efficient monitoring of patterns in data mining environments
TL;DR: In this paper, a general framework for monitoring patterns and detecting interesting changes without continuously mining the data is introduced, which is based on a temporal representation for patterns, in which both the content and the statistics of a pattern are modeled.
48
Using Health-Consumer-Contributed Data to Detect Adverse Drug Reactions by Association Mining with Temporal Analysis
Haodong Yang,Christopher C. Yang +1 more
TL;DR: The experiment results show that health-related social media is a promising source for ADR detection, and the proposed techniques are effective to identify early ADR signals.
44
Continuous preference trend mining for optimal product design with multiple profit cycles
Jungmok Ma,Harrison M. Kim +1 more
- 04 Aug 2013
TL;DR: The proposed continuous preference trend mining algorithm and application enables design engineers to optimize product design over multiple life cycles while reflecting customer preferences and technological obsolescence using the CPTM algorithm.
28
References
Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.
Classification and regression trees
TL;DR: This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.
Mining association rules between sets of items in large databases
Rakesh Agrawal,Tomasz Imielinski,Arun N. Swami +2 more
- 01 Jun 1993
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.