Open AccessKnowledge Discovery on Trajectory Data Warehouses: Possible usage of the Data Mining Techniques
Author(s) -
Fernando José Braz
Publication year - 2008
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/sbsi.2008.5921
Subject(s) - computer science , data warehouse , trajectory , data mining , knowledge extraction , volume (thermodynamics) , set (abstract data type) , data stream mining , order (exchange) , data science , data stream , data set , artificial intelligence , physics , finance , quantum mechanics , astronomy , economics , programming language , telecommunications
In this paper we are interested in discussing the possibility of theusage of Data Mining tasks in order to reveal knowledge resident in Trajectory Data Warehouses (TDW). We consider a data stream environment where a set of mobile objects send the data about its location in a irregular and unbounded way. The data volume is stored in a centralized and traditional DW with precomputed aggregations values (preserving the trajectories privacy). Through of analysis of the TDW measures (pre-computed aggregation values) we can reveal some characteristics about trajectories in a given spatio-temporal area. The revealed knowledge can be useful in order to describe or show the occurrence of a real phenomenon. We present a review of a proposed structure of a TDW and discuss the use of Data Mining tasks to improve the analysis of the trajectory data warehouse environment.