IIUM Repository (IREP)

CRF based feature extraction applied for supervised automatic text summarization

K. Batcha, Nowshath and A. Aziz, Normaziah and I. Shafie, Sharil (2013) CRF based feature extraction applied for supervised automatic text summarization. Procedia Technology , 11. pp. 426-436. ISSN 2212-0173

[img]
Preview
PDF - Published Version
Download (1130Kb) | Preview

    Abstract

    Feature extraction is the promising issue to be addressed in algebraic based Automatic Text Summarization (ATS) methods. The most vital role of any ATS is the identification of most important sentences from the given text. This is possible only when the correct features of the sentences are identified properly. Hence this paper proposes a Conditional Random Field (CRF) based ATS which can identify and extract the correct features which is the main issue that exists with the Non-negative Matrix Factorization (NMF) based ATS. This work proposes a trainable supervised method. Result clearly indicates that the newly proposed approach can identify and segment the sentences based on features more accurately than the existing method addressed.

    Item Type: Article (Journal)
    Additional Information: 5505/35423
    Uncontrolled Keywords: Automatic Text Summarization;Information Overload;Summarization; Feature extraction
    Subjects: T Technology > T Technology (General) > T10.5 Communication of technical information
    Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Information and Communication Technology > Department of Computer Science
    Kulliyyah of Information and Communication Technology > Department of Computer Science
    Depositing User: Assoc. Prof. Dr Normaziah Abdul Aziz
    Date Deposited: 06 Feb 2014 14:21
    Last Modified: 15 Sep 2014 10:41
    URI: http://irep.iium.edu.my/id/eprint/35423

    Actions (login required)

    View Item