Abstract
Some of the attributes of a database relation may evolve over time i.e., they change their values at different instants of time. For example, affiliation attribute of an author relation in a bibliographic database which maintains publication details of various authors, may change its value. When a database contains records of this nature and number of records grows to a large extent then it becomes really very challenging to identify which records belong to which entity due to lack of a proper key. In such a situation, the other attributes of the records and the timed information associated with the records may be useful in identifying whether the records belong to the same entity or different. In the proposed work, the records are initially clustered based on email-id attribute and the clusters are further refined based on other temporal and non-temporal attributes. The refinement process involves similarity check with other records and clusters. A comparative analysis with two existing systems DBLP and ArnetMiner shows that the proposed technique can able to produce better results in many cases.
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Mishra, S., Mondal, S., Saha, S. (2013). Entity Matching Technique for Bibliographic Database. In: Decker, H., Lhotská, L., Link, S., Basl, J., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 2013. Lecture Notes in Computer Science, vol 8056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40173-2_5
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DOI: https://doi.org/10.1007/978-3-642-40173-2_5
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