Mining interesting patterns in multi-relational data with N-ary relationships

Eirini Spyropoulou, Tijl De Bie, Mario Boley

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

10 Citations (Scopus)


We present a novel method for mining local patterns from multi-relational data in which relationships can be of any arity. More specifically, we define a new pattern syntax for such data, develop an efficient algorithm for mining it, and define a suitable interestingness measure that is able to take into account prior information of the data miner. Our approach is a strict generalisation of prior work on multi-relational data in which relationships were restricted to be binary, as well as of prior work on local pattern mining from a single n-ary relationship. Remarkably, despite being more general our algorithm is comparably fast or faster than the state-of-the-art in these less general problem settings.

Original languageEnglish
Title of host publicationDiscovery Science - 16th International Conference, DS 2013 Singapore, October 6-9, 2013 Proceedings
EditorsJohannes Fürnkranz, Eyke Hüllermeier, Tomoyuki Higuchi
Place of PublicationBerlin Germany
Number of pages16
ISBN (Electronic)9783642408977
ISBN (Print)9783642408960
Publication statusPublished - 2013
Externally publishedYes
EventInternational Conference on Discovery Science 2013 - Singapore, Singapore
Duration: 6 Oct 20139 Oct 2013
Conference number: 16th

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Discovery Science 2013
Abbreviated titleDS 2013
Internet address

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