Abstract
Today, bibliographic digital libraries play an important role in helping members of academic community search for novel research. In particular, author disambiguation for citations is a major problem during the data integration and cleaning process, since author names are usually very ambiguous. For solving this problem, we proposed two kinds of correlations between citations, namely, Topic Correlation and Web Correlation, to exploit relationships between citations, in order to identify whether two citations with the same author name refer to the same individual.The topic correlation measures the similarity between research topics of two citations; while the Web correlation measures the number of co-occurrence in web pages. We employ a pair-wise grouping algorithm to group citations into clusters. The results of experiments show that the disambiguation accuracy has great improvement when using topic correlation and Web correlation, and Web correlation provides stronger evidences about the authors of citations.
This work was supported in part by the National Digital Archive Program (NDAP, Taiwan), the National Science Council of Taiwan under grants NSC 96-2628-E-011-084-MY3, NSC 96-2221-E-011-064-MY3, NSC 95-3114-P-001-002-Y02, NSC95-3114-P-001-001-Y02 and NSC 95-2221-E-001-021-MY3.
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Yang, KH., Peng, HT., Jiang, JY., Lee, HM., Ho, JM. (2008). Author Name Disambiguation for Citations Using Topic and Web Correlation. In: Christensen-Dalsgaard, B., Castelli, D., Ammitzbøll Jurik, B., Lippincott, J. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2008. Lecture Notes in Computer Science, vol 5173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87599-4_19
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DOI: https://doi.org/10.1007/978-3-540-87599-4_19
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