Title :
Investigating the Use of Semantic-Based Websites to Improve Recommendation Quality
Author :
Eimuri, Taees ; Salehi, Sara
Author_Institution :
Islamic Azad Univ. of Parand, Parand, Iran
Abstract :
In this paper, we aim to investigate the use of semantic-based websites to improve recommendation quality by testing a knowledge based recommendation system whose results completely depends on the product descriptions, on two different databases. In one of our relational MySQL databases, product descriptions are stored in form of RDF files and in the other one the data is stored in human language. We show that, the RS results are more accurate and intelligent when it is working with the semantic based database that stores product information in form of RDF graphs. Since, the well-defined data can help the recommendation system to analyze an extract the data better and make "smart" decisions.
Keywords :
SQL; Web sites; knowledge based systems; recommender systems; relational databases; semantic Web; software quality; RDF files; knowledge based recommendation system; product descriptions; recommendation quality improvement; relational MySQL databases; semantic based Websites; Collaboration; Electronic commerce; Filtering; Humans; Machine learning; Ontologies; Relational databases; Resource description framework; Semantic Web; Taxonomy; Ecommerce; RDF; Recommendation Systems; Semantic Web; semantic-based websites;
Conference_Titel :
Computer Research and Development, 2010 Second International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-0-7695-4043-6
DOI :
10.1109/ICCRD.2010.48