Using Laplace and angular measures for Feature Selection in Text Categorisation. (21st October 2008)
- Record Type:
- Journal Article
- Title:
- Using Laplace and angular measures for Feature Selection in Text Categorisation. (21st October 2008)
- Main Title:
- Using Laplace and angular measures for Feature Selection in Text Categorisation
- Authors:
- Montanes, Elena
Alonso, Pedro
Combarro, Elias F.
Diaz, Irene
Cortina, Raquel
Ranilla, Jose - Abstract:
- Text Categorisation (TC) consists of automatically assigning documents to a set of prefixed categories. It usually involves the management of a huge number of features. Some of them are irrelevant or noisy which mislead the classifiers. Thus, they are reduced to increase the efficiency and effectiveness of the classification. In this paper we propose to select relevant features using two different families of filtering measures, which are simpler than other usual measures applied for this purpose. The experiments over three corpora show that, in general, the proposed measures perform equal or better than the existing ones, sometimes allowing greater reductions.
- Is Part Of:
- International journal of advanced intelligence paradigms. Volume 1:Number 1(2008)
- Journal:
- International journal of advanced intelligence paradigms
- Issue:
- Volume 1:Number 1(2008)
- Issue Display:
- Volume 1, Issue 1 (2008)
- Year:
- 2008
- Volume:
- 1
- Issue:
- 1
- Issue Sort Value:
- 2008-0001-0001-0000
- Page Start:
- 40
- Page End:
- 59
- Publication Date:
- 2008-10-21
- Subjects:
- feature selection -- text categorisation -- polynomial filtering measures
Artificial intelligence -- Periodicals
Machine theory -- Periodicals
Fuzzy logic -- Periodicals
006.305 - Journal URLs:
- http://www.inderscience.com/browse/index.php?journalID=272 ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 1755-0386
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 8139.xml