Abstract
Text information processing depends critically on the proper representation of documents. Traditional models, like the vector space model, have significant limitations because they do not consider semantic relations amongst terms. In this paper we analyze a document representation using the association graph scheme and present a new approach called Global Association Distance Model (GADM). At the end, we compare GADM using K-NN classifier with the classical vector space model and the association graph model.
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Medina-Pagola, J.E., Rodríguez, A.Y., Hechavarría, A., Hernández Palancar, J. (2007). Document Representation Using Global Association Distance Model. In: Amati, G., Carpineto, C., Romano, G. (eds) Advances in Information Retrieval. ECIR 2007. Lecture Notes in Computer Science, vol 4425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71496-5_52
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DOI: https://doi.org/10.1007/978-3-540-71496-5_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71494-1
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