id: 06016959
dt: j
an: 06016959
au: Yerva, Surender Reddy; Miklós, Zoltán; Aberer, Karl
ti: Quality-aware similarity assessment for entity matching in Web data.
so: Inf. Syst. 37, No. 4, 336-351 (2012).
py: 2012
pu: Elsevier Science (Pergamon), Amsterdam
la: EN
cc: 
ut: entity matching; Web; similarity functions; person name disambiguation;
    twitter message classification
ci: 
li: doi:10.1016/j.is.2011.09.007
ab: Summary: One of the key challenges to realize automated processing of the
    information on the Web, which is the central goal of the Semantic Web,
    is related to the entity matching problem. There are a number of tools
    that reliably recognize named entities, such as persons, companies,
    geographic locations, in Web documents. The names of these extracted
    entities are, however, non-unique; the same name on different Web pages
    might or might not refer to the same entity. The entity matching
    problem concerns of identifying the entities, which are referring to
    the same real-world entity. This problem is very similar to the entity
    resolution problem studied in relational databases, however, there are
    also several differences. Most importantly Web pages often only contain
    partial or incomplete information about the entities.
rv: