Abstract
Making search engines responsive to human needs requires understanding user intention when submitting a query. Intention, context and situation are intimately connected [8]. Thus context modelling is paramount when mining search engine logs but the process should be sistematized and standarized for the future generation of autonomous data mining components. In this paper, we propose to integrate context as metadata represented in PMML. The complete knowledge discovery process would benefit from the metadata and in particular final and intermediate evaluations can use this information for interpretation. The paper also presents results of integration of GUMO ontology to conceptualize user context to improve interpretation of query mining on the weblogs of the site search engine.
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Eibe, S., Valencia, M., Menasalvas, E., Segovia, J., Sousa, P. (2007). Towards User Context Enhance Search Engine Logs Mining. In: Wegrzyn-Wolska, K.M., Szczepaniak, P.S. (eds) Advances in Intelligent Web Mastering. Advances in Soft Computing, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72575-6_15
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DOI: https://doi.org/10.1007/978-3-540-72575-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72574-9
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