Accurately determining whether two Friend Of A Friend (FOAF) descriptions describe the same person is crucial to the success of FOAF on the Semantic Web. Unless this is possible, FOAF descriptions of the same individual originating from disparate sources can not be merged together, or "smushed", into a single description. Without smushing, data remains locked within the silos of the originating FOAF descriptions, the holistic view is lost and less can logically be stated about any specific individual. Current approaches to smushing correctly recognize that people do not have a URI unique identifier and instead rely on inverse-functional properties (IFP), such as an email address, to act as a weaker proxy for a globally unique identifier upon which to join descriptions. In this paper we point out the inadequacy of this approach in a broad class of FOAF application areas relating to data mining and information extraction. We describe a method capable of smushing numerous automatically extracted partial FOAF descriptions from disparate sources where suitable IFPs are unavailable.
|Translated title of the contribution||Estimating whether partial FOAF descriptions describe the same individual|
|Title of host publication||Workshop on Friend of a Friend, Social Networking and the Semantic Web (FOAF2004), Galway, Ireland|
|Publication status||Published - 2004|