Publication:
Text Summarization Technique for Punjabi Language Using Neural Networks

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: GigaBDes
dc.contributor.authorJain, Arti
dc.contributor.authorArora, Anuja
dc.contributor.authorYadav, Divakar
dc.contributor.authorMorato Lara, Jorge Luis
dc.contributor.authorKaur, Amanpreet
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2023-07-05T10:47:37Z
dc.date.available2023-07-05T10:47:37Z
dc.date.issued2021-11-01
dc.description.abstractIn the contemporary world, utilization of digital content has risen exponentially. For example, newspaper and web articles, status updates, advertisements etc. have become an integral part of our daily routine. Thus, there is a need to build an automated system to summarize such large documents of text in order to save time and effort. Although, there are summarizers for languages such as English since the work has started in the 1950s and at present has led it up to a matured stage but there are several languages that still need special attention such as Punjabi language. The Punjabi language is highly rich in morphological structure as compared to English and other foreign languages. In this work, we provide three phase extractive summarization methodology using neural networks. It induces compendious summary of Punjabi single text document. The methodology incorporates pre-processing phase that cleans the text; processing phase that extracts statistical and linguistic features; and classification phase. The classification based neural network applies an activation function- sigmoid and weighted error reduction-gradient descent optimization to generate the resultant output summary. The proposed summarization system is applied over monolingual Punjabi text corpus from Indian languages corpora initiative phase-II. The precision, recall and F-measure are achieved as 90.0%, 89.28% an 89.65% respectively which is reasonably good in comparison to the performance of other existing Indian languages" summarizers.en
dc.description.sponsorshipThis research is partially funded by the Ministry of Economy, Industry and Competitiveness, Spain (CSO2017-86747-R).en
dc.identifier.bibliographicCitationJain, A., Arora, A., Yadav, D. Morado, J., Kaur, A. (2021). Text Summarization Technique for Punjabi Language Using Neural Networks. The International Arab Journal of Information Technology, 18(6), pp. 807-819).en
dc.identifier.doihttps://doi.org/10.34028/iajit/18/6/8
dc.identifier.issn1683-3198
dc.identifier.publicationfirstpage807
dc.identifier.publicationissue6
dc.identifier.publicationlastpage818
dc.identifier.publicationtitleInternational Arab Journal of Information Technologyen
dc.identifier.publicationvolume18
dc.identifier.urihttps://hdl.handle.net/10016/37752
dc.identifier.uxxiAR/0000031154
dc.language.isoeng
dc.publisherIAJITen
dc.relation.projectIDGobierno de España. CSO2017-86747-Res
dc.rights© IAJIT, 2021en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.otherextractive methoden
dc.subject.otherindian languages corpora initiativeen
dc.subject.othernatural language processingen
dc.subject.otherneural networksen
dc.subject.otherpunjabi languageen
dc.subject.othertext summarizationen
dc.titleText Summarization Technique for Punjabi Language Using Neural Networksen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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