A fusion of variants of sentence scoring methods and collaborative word rankings for document summarization. Issue 6 (16th February 2022)
- Record Type:
- Journal Article
- Title:
- A fusion of variants of sentence scoring methods and collaborative word rankings for document summarization. Issue 6 (16th February 2022)
- Main Title:
- A fusion of variants of sentence scoring methods and collaborative word rankings for document summarization
- Authors:
- Verma, Pradeepika
Verma, Anshul
Pal, Sukomal - Other Names:
- Montenegro‐Marin Carlos Enrique guestEditor.
Gaona‐Garcia Paulo Alonso guestEditor.
Nuñez Valdez Edward Rolando guestEditor.
Gao Honghao guestEditor.
Zhang Yudong guestEditor.
Hussain Walayat guestEditor. - Abstract:
- Abstract: Document summarization is an important task in natural language processing that helps deal with the problem of information overload occurring due to the existence of redundant content. Summary generation with highly relevant contents and maximum coverage is particularly challenging which can only be achieved when redundancy is minimized. This article introduces a novel approach for automatic text summarization based on sentence scoring and collaborative ranking to produce summaries with minimal redundancy and improved overall performance of summarization. The proposed model is a fusion of weighted and unweighted features‐based sentence scoring methods. To learn optimal weights of text features, it has been modelled as an optimization problem. Moreover, the proposed model exploits the strength of collaborative ranking to generate the summary of a given document. Three similarity factors (proximity, significance and singularity)‐based models have been employed to find the similarity between weighted and unweighted sentence scores. The results of the comparison experiment demonstrate that the proposed (PS + Jac) method generates a closer summary to the reference summary with minimal redundant contents. On average, the proposed (PS + Jac) method generates the summaries with 61% accurate contents with greater improved rates up to 40%. The statistical testing also confirms that the performance improvement is significant at a 5% level of significance.
- Is Part Of:
- Expert systems. Volume 39:Issue 6(2022)
- Journal:
- Expert systems
- Issue:
- Volume 39:Issue 6(2022)
- Issue Display:
- Volume 39, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 39
- Issue:
- 6
- Issue Sort Value:
- 2022-0039-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-02-16
- Subjects:
- collaborative ranking -- document summarization -- Jaya -- proximity -- redundancy -- significance
Expert systems (Computer science)
006.33 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1468-0394 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/exsy.12960 ↗
- Languages:
- English
- ISSNs:
- 0266-4720
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 22127.xml