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2016 | OriginalPaper | Buchkapitel

WRSP-Miner Algorithm for Mining Weighted Sequential Patterns from Spatio-temporal Databases

verfasst von : Gurram Sunitha, A. Rama Mohan Reddy

Erschienen in: Proceedings of the Second International Conference on Computer and Communication Technologies

Verlag: Springer India

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Abstract

Not allowing priorities in the mining process does not support user-directed or focus-driven mining. The work proposed in this paper provides support to include user prioritizations in the form of weights into the mining process. An algorithm WRSP-Miner is proposed for the purpose of mining Weighted Regional Sequential Patterns (WRSPs) from spatio-temporal event databases. WRSP-Miner uses two interestingness measures sequence weight and significance index for efficient mining of WRSPs. Experimentation has been performed on synthetic datasets and results proved that the proposed WRSP-Miner algorithm has achieved the purpose of its design.

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Metadaten
Titel
WRSP-Miner Algorithm for Mining Weighted Sequential Patterns from Spatio-temporal Databases
verfasst von
Gurram Sunitha
A. Rama Mohan Reddy
Copyright-Jahr
2016
Verlag
Springer India
DOI
https://doi.org/10.1007/978-81-322-2517-1_31