Using Support Vector Machines for feature-oriented profile-based recommendations. (26th June 2009)

• Record Type: Journal Article
• Authors: Garcia-Crespo, Angel; Gomez-Berbis, Juan Miguel; Colomo-Palacios, Ricardo; Garcia-Sanchez, Francisco
• Is Part Of: International journal of advanced intelligence paradigms. Volume 1:Number 4(2009)
• Page Start: 418
• Page End: 431
• Publication Date: 2009-06-26
• Subjects: recommendation systems -- SVM -- support vector machines -- semantic technologies -- artificial intelligence -- ubiquitous computing -- classification -- user profiling -- user profiles -- user preferences; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

Recommendations have reached a new dimension in a ubiquitous computing environment. A vast amount of information is coming from pervasive services and devices, providing a potential source of value-added knowledge. However, this knowledge must be exposed through a classification technique such as Support Vector Machines (SVMs), which would allow categorising, classifying and evaluating this information based on features and profiles to foster the efficiency of recommendations of informational items. This paper presents an algorithm based on SVMs and an underlying architecture to extract and build a number of recommendations based on features and profile preferences from the user.