Incremental unsupervised name disambiguation in cleaned digital libraries.
No Thumbnail Available
Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Name ambiguity in the context of bibliographic citation sisone of t h e hardest problems currently faced by the Digital Library ( DL) community. Here we deal with the problem of disambiguating new citations records insertedint o a cleaned DL, without the need t process the whole collection , which is usually necessary for un supervised methods. Although supervised solutions can deal with this situation , there is the costly burden of generating training data besides the fact that these methods cannot and le well the insertion of record s of new author not already existent in the repository. I n t h is article, we propose a new unsupervised method that identifies the correct author sof the new citation records to be inserted in a DL. The method is based on heuristics that are also used to identify whet her the new record s belong to authors already in t h e digital library or not , correctly identifying new authors in most cases. Our experiment al evaluation , using synthetic an d real data sets, shows gains of u p t o 19% when compared to a state- of- t h e- art method without the cost of having to disambiguate the whole DL at each new load ( as d on e by u n supervised methods) or the need for any train in g ( as d on e by supervised methods) .
Description
Keywords
Bibliographic citation, Digital library, Name libraries
Citation
CARVALHO, A. P. de et al. Incremental un supervised name disambiguation in cleaned digital libraries. Journal of Information and Data Management, v. 2, n. 3, p. 289-304, 2011. Disponível em: <http://seer.lcc.ufmg.br/index.php/jidm/article/viewFile/151/88>. Acesso em: 22 out. 2012