Abstract
Similarity measures are usually used to compare items and identify pairs or groups of similar individuals. The similarity measure strongly depends on the type of values to compare. We have faced the problem of considering that the information of the individuals is a sequence of events (i.e. sequences of web pages visited by a certain user or the personal daily schedule). Some measures for numerical sequences exist, but very few methods consider sequences of categorical data. In this paper, we present a new similarity measure for sequences of categorical labels and compare it with the previous approaches.
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Gómez-Alonso, C., Valls, A. (2008). A Similarity Measure for Sequences of Categorical Data Based on the Ordering of Common Elements. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2008. Lecture Notes in Computer Science(), vol 5285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88269-5_13
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DOI: https://doi.org/10.1007/978-3-540-88269-5_13
Publisher Name: Springer, Berlin, Heidelberg
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