Fuzzy Mobility Pattern Discovery fromTime SummarizedMoving Data
Autor: | Wu JW(吴俊伟), Wang L(王亮), Ku T(库涛), Hu KY(胡琨元) |
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Rok vydání: | 2013 |
Předmět: | |
Zdroj: | INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences. 5:975-983 |
ISSN: | 2233-9345 1976-3700 |
Popis: | The advance of object tracking technologies leads to huge volumes of spatiotemporal data collected in moving database. Hidden the moving database, there are many useful information and knowledge which could reveal the mobility behavior and surrounding conditions. In this paper, we focused on the problem of mining behavior pattern from time summarized moving data in which the temporal information is summarized in short period and represented by range values. Utilizing interval number calculating, we obtain time gap between any two consecutive records. Based on fuzzy set theory, we defined mobile behavior with fuzzy linguistic terms and corresponding support. Finally we proposed two mobile behavior mining algorithms improved by Apriori algorithm and PrefixSpan algorithm. The proposed methods are evaluated with extensive experiments on both real and synthetic datasets. |
Databáze: | OpenAIRE |
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