Abstract
Exploiting the cumulative behavior of users is a common technique used to improve many popular online services. We build a tag spell checker using a graph-based model. In particular, we present a novel technique based on the graph of tags associated with objects made available by online sites such as Flickr and YouTube. We show the effectiveness of our approach on the basis of an experimentation done on real-world data. We show a precision of up to 93% with a recall (i.e., the number of errors detected) of up to 100%.
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Nardini, F.M., Silvestri, F., Vahabi, H., Vahabi, P., Frieder, O. (2010). On Tag Spell Checking. In: Chavez, E., Lonardi, S. (eds) String Processing and Information Retrieval. SPIRE 2010. Lecture Notes in Computer Science, vol 6393. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16321-0_4
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DOI: https://doi.org/10.1007/978-3-642-16321-0_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16320-3
Online ISBN: 978-3-642-16321-0
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