• Journal of Information Management
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• v.42 no.1
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• pp.47-62
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• 2011

While an ideal author graph should have its nodes to represent authors, automatically-generated author graphs mostly use author names as their nodes due to the difficulty of resolving author names into individuals. However, employing author names as nodes of author graphs merges namesakes, otherwise separate nodes in the author graph, into the same node, which may distort the characteristics of the author graph. This study proposes an algorithm which resolves author ambiguities based on co-authorship and then yields an author graph consisting of not author name nodes but author nodes. Scientific collaboration relationship this algorithm depends on tends to produce the clustering results which minimize the over-clustering error at the expense of the under-clustering error. In experiments, the algorithm is applied to the real citation records where Korean namesakes occur, and the results are discussed.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.41-47
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• 2008

There exists a many-to-many mapping relationship between persons and their names. A person may have multiple names, and different persons may share the same name. These synonymous and homonymous names may severely deteriorate the recall and precision of the person search, respectively. This study addresses the characteristics of features for resolving homonymous author names appearing in citation data. As disambiguation features, previous works have employed citation-internal features such as co-authorship, titles of articles, titles of publications as well as citation-external features such as emails, affiliations, Web evidences. To the best of our knowledge, however, there has been no literature to deal with the influences of features on author disambiguation. This study analyzes the effect of individual features on author resolution using a large-scale test set for Korean.