Cart (Loading....) | Create Account
Close category search window

Mining Spatio-temporal Patterns in the Presence of Concept Hierarchies

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
2 Author(s)
Le Van Quoc Anh ; Inst. of Comput. Sci., Heidelberg Univ., Heidelberg, Germany ; Gertz, M.

In the past, approaches to mining spatial and spatio-temporal data for interesting patterns have mainly concentrated on data obtained through observations and simulations where positions of objects, such as areas, vehicles, or persons, are collected over time. In the past couple of years, however, new datasets have been built by automatically extracting facts, as subject-predicate-object triples, from semi structured information sources such as Wikipedia. Recently some approaches, for example, in the context of YAGO2, have extended such facts by adding temporal and spatial information. The presence of such new data sources gives rise to new approaches for discovering spatio-temporal patterns. In this paper, we present a framework in support of the discovery of interesting spatio-temporal patterns from knowledge base datasets. Different from traditional approaches to mining spatio-temporal data, we focus on mining patterns at different levels of granularity by exploiting concept hierarchies, which are a key ingredient in knowledge bases. We introduce a pattern specification language and outline an algorithmic approach to efficiently determine complex patterns. We demonstrate the utility of our framework using two different real-world datasets from YAGO2 and the Website

Published in:

Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on

Date of Conference:

10-10 Dec. 2012

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.