An error correction methodology for time dependent ontologies

Abstract

An increasing number of applications have become dependent upon information described in ontologies. Information may be correct for a limited period of time, for example, the assertion: "Barack Obama is the current president of the USA" will be incorrect in 2017. A presidential lifespan can be measured in years, however in a more dynamic domain, assertions may have lifespans of: months, weeks or days. In addition, erroneous relations may be introduced into an Ontology through mistakes in the information source or construction methodology. Ontologies which contain a large number of errors may impair the effectiveness of applications which depend on it. This paper describes an error correction methodology for ontologies automatically generated from news stories. The information contained in news stories can have a very limited lifespan, consequently constructing an Ontology by an addition of assertions will overtime accumulate errors. The proposed method avoids this problem through an assignment of a lifespan to each relation. A relation's lifespan is dependent upon: frequency of assertion, relation volatility and domain volatility. Once a relation's lifespan has elapsed the relation is either deleted or archived as a temporal "snapshot" of the domain. Individuals with 0 relations are also removed or archived. An evaluation of an Ontology constructed with the proposed scheme revealed a gain in the total number of relations overtime without an increase in the number of the errors. A comparison with an Ontology constructed with an accumulative addition of relations over an eight week period revealed that the proposed method reduced the error count by 81%. © 2011 Springer-Verlag.