The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Ontology-Based Optimization in Search Engine
|
|
Author(s): Leonardo Balduzzi (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)and Ignacio Cuesta (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)
Copyright: 2013
Pages: 17
Source title:
Advancing Information Management through Semantic Web Concepts and Ontologies
Source Author(s)/Editor(s): Patricia Ordóñez de Pablos (Universidad de Oviedo, Spain), Héctor Oscar Nigro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina), Robert D. Tennyson (University of Minnesota, USA), Sandra Elizabeth Gonzalez Cisaro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)and Waldemar Karwowski (University of Central Florida, USA)
DOI: 10.4018/978-1-4666-2494-8.ch015
Purchase
|
Abstract
The major aim of the chapter is to propose and study the use of ontology-based optimization for positioning websites in search engines. In this sense, using heterogeneous inductive learning techniques and ontology for knowledge representation, a knowledge-based system which is capable of supporting the activity of SEO (Search Engine Optimization) has been designed and implemented. From its knowledge base, the system suggests the most appropriate optimization tasks for positioning a pair (keyword, website) on the first page of search engines and infers the positioning results to be obtained. The system evolution and learning capacity allows optimizing the productivity and effectiveness of the SEO process.
Related Content
|
.
© 2020.
58 pages.
|
|
.
© 2020.
52 pages.
|
|
.
© 2020.
10 pages.
|
|
.
© 2020.
14 pages.
|
|
.
© 2020.
33 pages.
|
|
.
© 2020.
13 pages.
|
|
.
© 2020.
36 pages.
|
|
|