Incremental maintenance of topological patterns in spatial-temporal database

Yi Cheng Chen, Chao Ying Wu, Suh Yin Lee

研究成果: 書貢獻/報告類型會議論文篇章同行評審

2 引文 斯高帕斯(Scopus)

摘要

Spatial temporal mining is an important research area with many interesting topics. Most spatial temporal databases are updating incrementally with time. Some discovered topological patterns may be invalidated and some new topological patterns may be introduced by the evolution of databases. However, the existing static algorithms are usually inefficient and not feasible to maintain topological patterns in an incremental environment. In this paper, we develop an efficient algorithm, Inc-TMiner (Incremental Topology Miner) to incrementally maintain topological patterns in spatial-temporal databases. The experimental results indicate that Inc-TMiner significantly outperforms state-of-the-art algorithms in execution time and possesses graceful scalability.

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主出版物標題Proceedings - 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011
頁面853-860
頁數8
DOIs
出版狀態已出版 - 2011
事件11th IEEE International Conference on Data Mining Workshops, ICDMW 2011 - Vancouver, BC, Canada
持續時間: 11 12月 201111 12月 2011

出版系列

名字Proceedings - IEEE International Conference on Data Mining, ICDM
ISSN(列印)1550-4786

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???event.eventtypes.event.conference???11th IEEE International Conference on Data Mining Workshops, ICDMW 2011
國家/地區Canada
城市Vancouver, BC
期間11/12/1111/12/11

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