Towards faster activity search using embedding-based subsequence matching

Authors:
Panagiotis Papapetrou;Paul Doliotis;Vassilis Athitsos
Affiliations:
Boston University;University of Texas at Arlington;University of Texas at Arlington
Venue:
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
Year:
2009

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Abstract

Event search is the problem of identifying events or activity of interest in a large database storing long sequences of activity. In this paper, our topic is the problem of identifying activities of interest in databases where such activities are represented as time series. In the typical setup, the user presents a query that represents an activity of interest, and the system needs to retrieve the most similar activities stored in the database. We focus on the case where the best database matches are not segmented a priori: the database contains representations of long, continuous activity, that occurs throughout relatively extensive periods of time, and, given a query, there are no constraints as to when exactly a database match starts and ends within the longer activity pattern where it is contained. Using the popular DTW measure, the best database matches can be found using dynamic programming. However, retrieval time is linear to the size of the database and can become too long as the database size becomes larger. To achieve more efficient retrieval time, we apply to this problem a recently proposed technique called Embedding-based Subsequence Matching (EBSM), and we demonstrate that using EBSM we can obtain significant speedups in retrieval time.