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primary topic: A semi-supervised multi-label classification framework with feature reduction and enrichment

A semi-supervised multi-label classification framework with feature reduction and enrichment
type: AcademicArticle
type: Article
abstract: Multi-label classification has drawn much attention thanks to its usefulness and omnipresence in real-world applications in which objects may be char-acterized by more than one label as in the traditional approach. Getting mul-ti-label examples is costly and time-consuming therefore semi-supervised learning approach should be considered to take advantages of both labeled and unlabeled data. In this work, we propose a semi-supervised multi-label classification algorithm exploiting the specific features of the prominent class label(s) chosen by a greedy approach as an extension of the LIFT algo-rithm, and unlabeled data consumption mechanism from the TESC algo-rithm. We also make a semi-supervised multi-label classification application framework for Vietnamese texts with several feature enrichment steps in-cluding a) a stage of enriching features by adding hidden topic features; b) a stage of dimensional reduction for subtracting irrelevant features. Experi-mental results on a dataset of hotel reviews (for tourism) indicate that a rea-sonable amount of unlabeled data helps to increase the F1 score. Interesting-ly, with a small amount of labeled data, our algorithm can reach a compara-tive performance to the case of using a larger amount of labeled data.
date: 2017
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository
subject: Information Technology (IT)

Journal of Information and Telecommunication
type: Collection

Van Quang Nguyen
type: Person
given name: Van Quang
family name: Nguyen

Van Hien Tran
type: Person
given name: Van Hien
family name: Tran

Quang Thuy Ha
type: Person
given name: Quang Thuy
family name: Ha

Tri Thanh Nguyen
type: Person
given name: Tri Thanh
family name: Nguyen

Thi Ngan Pham
type: Person
given name: Thi Ngan
family name: Pham

HTML Summary of #2504 A semi-supervised multi-label classification framework with feature reduction and enrichment
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primary topic: A semi-supervised multi-label classification framework with feature reduction and enrichment

Information Technology (IT)
type: Concept