Knowledge Based System for Intelligent Search Engine Optimization

  • Héctor Oscar Nigro
  • Leonardo Balduzzi
  • Ignacio Andrés Cuesta
  • Sandra Elizabeth González Císaro
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 157)

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.

Keywords

Search Engine Inference Engine Optimization Task Business Rule Antecedent Part 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Héctor Oscar Nigro
    • 1
  • Leonardo Balduzzi
    • 1
  • Ignacio Andrés Cuesta
    • 1
  • Sandra Elizabeth González Císaro
    • 1
  1. 1.Department of Computer Sciences and Systems, Exacts Sciences FacultyUniversidad Nacional del Centro de la Provincia de Buenos AiresTandilArgentina

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