NDLI: Frequence: interactive mining and visualization of temporal frequent event sequences

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Frequence: interactive mining and visualization of temporal frequent event sequences

Content Provider	ACM Digital Library
Author	Wang, Fei Perer, Adam
Abstract	Extracting insights from temporal event sequences is an important challenge. In particular, mining frequent patterns from event sequences is a desired capability for many domains. However, most techniques for mining frequent patterns are ineffective for real-world data that may be low-resolution, concurrent, or feature many types of events, or the algorithms may produce results too complex to interpret. To address these challenges, we propose Frequence, an intelligent user interface that integrates data mining and visualization in an interactive hierarchical information exploration system for finding frequent patterns from longitudinal event sequences. Frequence features a novel frequent sequence mining algorithm to handle multiple levels-of-detail, temporal context, concurrency, and outcome analysis. Frequence also features a visual interface designed to support insights, and support exploration of patterns of the level-of-detail relevant to users. Frequence's effectiveness is demonstrated with two use cases: medical research mining event sequences from clinical records to understand the progression of a disease, and social network research using frequent sequences from Foursquare to understand the mobility of people in an urban environment.
Starting Page	153
Ending Page	162
Page Count	10
File Format	PDF
ISBN	9781450321846
DOI	10.1145/2557500.2557508
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-02-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Frequent sequence mining Visual analytics Temporal visualization
Content Type	Text
Resource Type	Article

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