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Contrastive antichains in hierarchies

Authors :
Céline Robardet
Anes Bendimerad
Jefrey Lijffijt
Marc Plantevit
Tijl De Bie
Data Mining and Machine Learning (DM2L)
Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS)
Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)
Université de Lyon-École Centrale de Lyon (ECL)
Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Université Lumière - Lyon 2 (UL2)
Department of Electronics and Information Systems - Ghent University (ELIS)
Universiteit Gent = Ghent University [Belgium] (UGENT)
Source :
SIGKDD 2019, SIGKDD 2019, Aug 2019, Anchorage, Alaska, United States. pp.294:304, ⟨10.1145/3292500.3330954⟩, KDD, KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

International audience; Concepts are often described in terms of positive integer-valued attributes that are organized in a hierarchy. For example, cities can be described in terms of how many places there are of various types (e.g. nightlife spots, residences, food venues), and these places are organized in a hierarchy (e.g. a Portuguese restaurant is a type of food venue). This hierarchy imposes particular constraints on the values of related attributes---e.g. there cannot be more Portuguese restaurants than food venues. Moreover, knowing that a city has many food venues makes it less surprising that it also has many Portuguese restaurants, and vice versa. In the present paper, we attempt to characterize such concepts in terms of so-called contrastive antichains: particular kinds of subsets of their attributes and their values. We address the question of when a contrastive antichain is interesting, in the sense that it concisely describes the unique aspects of the concept, and this while duly taking into account the known attribute dependencies implied by the hierarchy. Our approach is capable of accounting for previously identified contrastive antichains, making iterative mining possible. Besides the interestingness measure, we also present an algorithm that scales well in practice, and demonstrate the usefulness of the method in an extensive empirical results section.

Details

Language :
English
ISBN :
978-1-4503-6201-6
ISBNs :
9781450362016
Database :
OpenAIRE
Journal :
SIGKDD 2019, SIGKDD 2019, Aug 2019, Anchorage, Alaska, United States. pp.294:304, ⟨10.1145/3292500.3330954⟩, KDD, KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING
Accession number :
edsair.doi.dedup.....770ff530ac2a293234910c9c7cf94f52
Full Text :
https://doi.org/10.1145/3292500.3330954⟩