Detect Time Series Sequences by Using Pattern Discovery
A S Prabaharan · 2014
Periodic pattern detection in time-ordered sequences is an important data mining task, which discovers in the time series all patterns that exhibit temporal regularities. Periodic pattern mining has a large number of applications in real life; it helps understanding the regular trend of the data along time, and enables the forecast and prediction of future events. An interesting related and vital problem that has not received enough attention is to discover outlier periodic patterns in a time series. A mining method to extract frequent patterns of human interaction based on the captured content of face-to-face meetings. Tree-based mining method for discovering frequent patterns of human interaction in meeting discussions. The mining results would be useful for summarization, indexing, and comparison of meeting records. Hidden interactions are discovered as patterns and the pattern is extracted to give pattern value. Captured meeting videos are converted into frames. Patterns are represented as frames and each frames are represented as snapshots.