Abstract: The problem of author name ambiguity in digital bibliography repositories can compromise the integrity and reliability of data. There are several techniques available in the literature to solve the author name disambiguation problem. In this work, we present a multi-strategic approach for author name disambiguation in bibliography repositories applying comparison of strings with the Jaccard similarity coefficient, Levenshtein distance measure, and social network clustering technique. Information from the DBLP digital bibliography repository is used to compare disambiguation results to SCI-synergy, an online scientific social network analysis artifact. The proposed approach outperforms the baseline with a precision of 0.8867, recall of 1, and F-measure of 0.9399, considering a Brazilian graduate program case.
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