Abstract
This paper presents a Knowledge-Based System that using heterogeneous inductive learning techniques and domain knowledge representation, has the major aim of supporting the activity of SEO (Search Engine Optimization). The system arises from the need to answer the following questions. Is it possible to position a web site without being an expert in SEO? Is it possible for a SEO tool to indicate what factors should be modified to position a web site? It attempts to answer both questions from a Domain Knowledge Base and an Inductive Knowledge Base by which the system suggests the most appropriate optimization tasks for positioning a pair [keyword, web site] on the first page of search engines and infers the positioning results to be obtained.
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© 2012 Springer-Verlag Berlin Heidelberg
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Nigro, H.O., Balduzzi, L., Cuesta, I.A., González Císaro, S.E. (2012). Knowledge Based System for Intelligent Search Engine Optimization. In: Gaol, F. (eds) Recent Progress in Data Engineering and Internet Technology. Lecture Notes in Electrical Engineering, vol 157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28798-5_10
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DOI: https://doi.org/10.1007/978-3-642-28798-5_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28797-8
Online ISBN: 978-3-642-28798-5
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