Home // IMMM 2013, The Third International Conference on Advances in Information Mining and Management // View article

Clustering Algorithms and Weighted Instance Based Learner for User Profiling

Authors:
Ayse Cufoglu
Mahi Lohi
Colin Everiss

Keywords: User Profiling; Weighted Instance Based Learner (WIBL); Clustering Algorithms

Abstract:
User profiling has created opportunities for service providers to make available a channel for user awareness as well as to achieve high user satisfaction. Apart from traditional collaborative and content-based methods, a number of classification and clustering algorithms have been used for user profiling. In our previous work, a weighted classification method, namely Weighted Instance Based Learner (WIBL), was proposed and evaluated for user profiling. In this paper, we aim to compare the performance of a WIBL algorithm with well known clustering algorithms for user profiling. Simulations showed that a WIBL is capable of outperforming the clustering algorithms.

Pages: 7 to 11

Copyright: Copyright (c) IARIA, 2013

Publication date: November 17, 2013

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-311-7

Location: Lisbon, Portugal

Dates: from November 17, 2013 to November 21, 2013