Improved Algorithm of Association Mining and Classification Fusion based on Temporal Interval Lattice

DOI

10.2991/meici-18.2018.114How to use a DOI?

Keywords

Association mining; Classification; Clustering; Temporal interval; Data mining

Abstract

This paper first describes the combined application of association rules data mining algorithm under temporal constraints. Clustering is to classify a group of individuals into several categories according to similarity. The purpose of clustering is to make the differences between individuals belonging to the same category as small as possible. The paper presents improved algorithm of Association Mining and Classification Fusion based on temporal interval Lattice. The database structure includes at least three fields: transaction number, temporal interval and item sequence. The temporal interval of this paper reflects the time range of the occurrence or collection of corresponding item sequences.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qing Tan
PY  - 2018/12
DA  - 2018/12
TI  - Improved Algorithm of Association Mining and Classification Fusion based on Temporal Interval Lattice
BT  - Proceedings of the 2018 8th International Conference on Management, Education and Information (MEICI 2018)
PB  - Atlantis Press
SP  - 578
EP  - 582
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-18.2018.114
DO  - 10.2991/meici-18.2018.114
ID  - Tan2018/12
ER  -