chapter

A Mining Algorithm Using Property Items Extracted from Sampled Examples

Authors:

Jun-Ichi Motoyama,

Shinpei Urazawa,

Tomofumi Nakano,

Nobuhiro InuzukaAuthors Info & Claims

Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers

March 2007

Pages 335 - 350

https://doi.org/10.1007/978-3-540-73847-3_32

Published: 01 March 2007 Publication History

Abstract

This paper proposes a mining algorithm for relational frequent patterns based on a bottom-up property extraction from examples. The extracted properties, called property items, are used to construct patterns by a level-wise way like Apriori. The property items are assumed to have a special form, which is defined in terms of mode declaration of predicates. The algorithm produces frequent itemsets as patterns without duplication in the sense of logical equivalence. It is implemented as a system called <Emphasis Type="SmallCaps">Mapix</Emphasis>and is evaluated with four different datasets with comparison to <Emphasis Type="SmallCaps">Warmr</Emphasis>. <Emphasis Type="SmallCaps">Mapix</Emphasis>had large advantage in runtime.

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Uno AItoh TCho YShin SKim SHung CHong J(2014)MALLProceedings of the 29th Annual ACM Symposium on Applied Computing10.1145/2554850.2554861(939-944)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2554850.2554861
Nakano YInuzuka N(2010)Multi-relational pattern mining based-on combination of properties with preserving their structure in examplesProceedings of the 20th international conference on Inductive logic programming10.5555/2022735.2022758(181-189)Online publication date: 27-Jun-2010
https://dl.acm.org/doi/10.5555/2022735.2022758
Seki HHonda YNagano S(2010)On enumerating frequent closed patterns with key in multi-relational dataProceedings of the 13th international conference on Discovery science10.5555/1927300.1927306(72-86)Online publication date: 6-Oct-2010
https://dl.acm.org/doi/10.5555/1927300.1927306
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A Mining Algorithm Using Property Items Extracted from Sampled Examples
1. Information systems
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Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers

March 2007

453 pages

ISBN:9783540738466

Publisher

Springer-Verlag

Berlin, Heidelberg

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Published: 01 March 2007

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Uno AItoh TCho YShin SKim SHung CHong J(2014)MALLProceedings of the 29th Annual ACM Symposium on Applied Computing10.1145/2554850.2554861(939-944)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2554850.2554861
Nakano YInuzuka N(2010)Multi-relational pattern mining based-on combination of properties with preserving their structure in examplesProceedings of the 20th international conference on Inductive logic programming10.5555/2022735.2022758(181-189)Online publication date: 27-Jun-2010
https://dl.acm.org/doi/10.5555/2022735.2022758
Seki HHonda YNagano S(2010)On enumerating frequent closed patterns with key in multi-relational dataProceedings of the 13th international conference on Discovery science10.5555/1927300.1927306(72-86)Online publication date: 6-Oct-2010
https://dl.acm.org/doi/10.5555/1927300.1927306
Inuzuka NMakino T(2010)Multi-relational pattern mining system for general database systemsProceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III10.5555/1885450.1885462(72-80)Online publication date: 8-Sep-2010
https://dl.acm.org/doi/10.5555/1885450.1885462
Inuzuka NMotoyama JUrazawa SNakano T(2008)Relational pattern mining based on equivalent classes of properties extracted from samplesProceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining10.5555/1786574.1786631(582-591)Online publication date: 20-May-2008
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Association rule mining and quantitative association rule mining among infrequent items

Association rule and quantitative association rule mining among infrequent items

Mining periodic-frequent patterns with maximum items' support constraints

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