Abstract
String matching is a fundamental operation in many applications such as data integration, information retrieval and text mining. Since users express the same meaning in a variety of ways that are not textually similar, existing works have proposed variants of Jaccard similarity by using synonyms to consider semantics beyond textual similarities. However, they may produce a non-negligible number of false positives in some applications by employing set semantics and miss some true positives due to approximations. In this paper, we define new match relationships between a pair of strings under synonym rules and develop an efficient algorithm to verify the match relationships for a pair of strings. In addition, we propose two filtering methods to prune non-matching string pairs. We also develop join algorithms with synonyms based on the filtering methods and the match relationships. Experimental results with real-life datasets confirm the effectiveness of our proposed algorithms.
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Acknowledgements
This research was supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2017M3C4A7063570).
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Song, G., Lee, H., Shim, K., Park, Y., Kim, W. (2020). String Joins with Synonyms. In: Nah, Y., Cui, B., Lee, SW., Yu, J.X., Moon, YS., Whang, S.E. (eds) Database Systems for Advanced Applications. DASFAA 2020. Lecture Notes in Computer Science(), vol 12114. Springer, Cham. https://doi.org/10.1007/978-3-030-59419-0_24
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DOI: https://doi.org/10.1007/978-3-030-59419-0_24
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