An efficient framework of utilizing the latent semantic analysis in text extraction
- Submitting institution
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The University of Huddersfield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11
- Type
- D - Journal article
- DOI
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10.1007/s10772-019-09623-8
- Title of journal
- International Journal of Speech Technology
- Article number
- -
- First page
- 785
- Volume
- 22
- Issue
- 3
- ISSN
- 1381-2416
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2019
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- An output of an interdisciplinary project in Computer science and Linguistics, the novelty in this paper is in the use of a multilayer similarity computation within the text extraction process. It features thorough and rigorous evaluation, using datasets of the Arabic language. The success of this research project led to future publications from the authors (e.g. non-submitted IJCSIS journal paper https://arxiv.org/abs/2004.13136) and PhD student co-author Ahmad Hussein Ababneh becoming a Lecturer at Prince SattamBin Abdel Aziz University, ALkharj, Saudi Arabia.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -