Redescription Mining for Learning Definitions and Disjointness Axioms in Linked Open Data

In this article, we present an original use of Redescription Mining (RM) for discovering definitions of classes and incompatibility (disjointness) axioms between classes of individuals in the web of data. RM is aimed at mining alternate descriptions from two datasets related to the same set of individuals. We reuse this process for providing definitions in terms of necessary and sufficient conditions to categories in DBpedia. Firstly, we recall the basics of redescription mining and make precise the principles of our definitional process. Then we detail experiments carried out on datasets extracted from DBpedia. Based on the output of the experiments, we discuss the strengths and the possible extensions of our approach.

[1]  Mehwish Alam,et al.  Interactive exploration over RDF data using formal concept analysis , 2015, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

[2]  Johanna Völker,et al.  Statistical Schema Induction , 2011, ESWC.

[3]  Heiko Paulheim,et al.  Type Inference on Noisy RDF Data , 2013, SEMWEB.

[4]  Nicola Fanizzi,et al.  Approximate classification with web ontologies through evidential terminological trees and forests , 2018, Int. J. Approx. Reason..

[5]  Johanna Völker,et al.  Automatic acquisition of class disjointness , 2015, J. Web Semant..

[6]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[7]  Fabian M. Suchanek,et al.  Are All People Married?: Determining Obligatory Attributes in Knowledge Bases , 2018, WWW.

[8]  Diego Calvanese,et al.  The Description Logic Handbook , 2007 .

[9]  Bernhard Ganter,et al.  Pattern Structures and Their Projections , 2001, ICCS.

[10]  Mehwish Alam,et al.  Mining Definitions from RDF Annotations Using Formal Concept Analysis , 2015, IJCAI.

[11]  Amedeo Napoli,et al.  Three Approaches for Mining Definitions from Relational Data in the Web of Data , 2018, FCA4AI@IJCAI.

[12]  Pauli Miettinen,et al.  From black and white to full color: extending redescription mining outside the Boolean world , 2012, Stat. Anal. Data Min..

[13]  Fabian M. Suchanek,et al.  AMIE: association rule mining under incomplete evidence in ontological knowledge bases , 2013, WWW.

[14]  Nicola Fanizzi,et al.  Terminological Cluster Trees for Disjointness Axiom Discovery , 2017, ESWC.

[15]  Jens Lehmann,et al.  DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia , 2015, Semantic Web.

[16]  Fabian M. Suchanek,et al.  Fast rule mining in ontological knowledge bases with AMIE+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$+$$\end{docu , 2015, The VLDB Journal.