Title

Personalized Classification for Keyword-based Category Profiles

Publication Type

Conference Proceeding Article

Publication Date

9-2002

Abstract

Personalized classification refers to allowing users to define their own categories and automating the assignment of documents to these categories. In this paper, we examine the use of keywords to define personalized categories and propose the use of Support Vector Machine (SVM) to perform personalized classification. Two scenarios have been investigated. The first assumes that the personalized categories are defined in a flat category space. The second assumes that each personalized category is defined within a pre-defined general category that provides a more specific context for the personalized category. The training documents for personalized categories are obtained from a training document pool using a search engine and a set of keywords. Our experiments have delivered better classification results using the second scenario. We also conclude that the number of keywords used can be very small and increasing them does not always lead to better classification performance.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

Research and Advanced Technology for Digital Libraries: 6th European Conference, ECDL 2002 Rome, Italy, September 16–18, 2002 Proceedings

Volume

2458

First Page

61

Last Page

74

ISBN

9783540457473

Identifier

10.1007/3-540-45747-X_5

Publisher

Springer Verlag

City or Country

Rome

Additional URL

http://dx.doi.org/10.1007/3-540-45747-X_5