1. Aidan Hogan, Antoine Zimmermann, Jürgen Umbrich, Axel Polleres, Stefan Decker Presented by Joseph Park SCALABLE AND DISTRIBUTED METHODS FOR ENTITY MATCHING, CONSOLIDATION AND DISAMBIGUATION OVER LINKED DATA CORPORA

2.  Linked Data best practices:  Use URIs as names for things (not just documents)  Make those URIs dereferenceable via HTTP  Return useful and relevant RDF content upon lookup of those URIs  Include links to other datasets  Linked Open Data project  Goal of providing dereferenceable machine readable data in RDF  Emphasis on reuse of URIs and inter-linkage between remote datasets  Web of Data  30 billion published RDF triples INTRODUCTION

3.  Focus on finding equivalent entities  E.g. people, places, musicians, proteins  Two entities are equivalent if they are coreferent  Interest in identifying coreferences and merge knowledge contributions provided by distinct parties (consolidation) AIMS & GOALS

4.  owl:sameAs  A core OWL property that defines equivalences between individuals  Two individuals related by owl:sameAs are coreferent  Inferring new owl:sameAs relations:  Inverse-functional properties (e.g :biologicalMotherOf)  Functional properties (e.g :hasBiologicalMother)  Cardinality and max-cardinality restrictions OWL:SAMEAS

5. CONSTRAINTS TO OWL:SAMEAS

6.  1.118 billion quadruples  Crawled from 3.985 million web documents  1.106 billion are unique  947 million are unique triples  9 machines linked by Gigabit ethernet EXPERIMENT

7.  Extracted 11.93 million raw owl:sameAs quadruples  Only 3.77 million unique triples  1000 randomly chosen pairs hand-checked  Trivially same (661 times)  Same (301 times)  Different (28 times)  Unclear (10 times) BASELINE – OWL:SAMEAS

8.  No documents used owl:maxQualifiedCardinality  434 functional properties  57 inverse-functional properties  109 cardinality restrictions with a value of 1  52.93 million memberships of inverse-functional properties  22.14 million asserted  11.09 million memberships of functional properties  1.17 million asserted  2.56 million cardinality triples  533 thousand asserted CONSTRAINT COUNTS

9.  Zero owl:sameAs inferences through cardinality rules  106.8 thousand owl:sameAs through functional-property reasoning  8.7 million owl:sameAs through inverse-functional-property reasoning  Resulted in a total of 12.03 million owl:sameAs statements REASONING USING CONSTRAINTS

10.  From the 12.03 million owl:sameAs quadruples  1000 randomly chosen and hand-checked:  Trivially same (145 times)  Same (823 times)  Different (23 times)  Unclear (9 times) RESULTS FROM CONSTRAINTS

11.  Entity concurrence—sharing of outlinks, inlinks, and attribute values  Higher score means more discriminating shared characteristics STATISTICAL CONCURRENCE

12. RUNNING EXAMPLE

13.  Observed cardinality (e.g. Card_G_ex (foaf:maker; dblp:AliceB10) = 2)  Observed inverse-cardinality (e.g. ICard_G_ex (foaf:gender; "female") = 2)  Average inverse-cardinality (e.g. AIC_G_ex (foaf:gender) = 1.5)  Can also be viewed as average non-zero cardinalities  For example, foaf:gender; 1 for “male”, 2 for “female” QUANTIFYING CONCURRENCE

14. ADJUSTED AVERAGE INVERSE- CARDINALITY

15. CONCURRENCE COEFFICIENTS

16. COEFFICIENT EXAMPLE

17. AGGREGATED CONCURRENCE SCORE

18.  Average cardinality of about 1.5  Average inverse-cardinality of about 2.64  Total of 636.9 million weighted concurrence pairs  Mean concurrence weight of about 0.0159  Highly concurring entities were in many cases not coreferent RESULTS FROM CONCURRENCE

19. EXAMPLE OF CONCURRENCE