A select and rewrite approach to the generation of related work reports
| dc.contributor.author | AbuRa'ed, Ahmed Ghassan Tawfiq | |
| dc.contributor.author | Saggion, Horacio | |
| dc.date.accessioned | 2021-05-19T07:47:40Z | |
| dc.date.available | 2021-05-19T07:47:40Z | |
| dc.date.issued | 2021 | |
| dc.description | Comunicació presentada al BIR 2021: 11th International Workshop on Bibliometric-enhanced Information Retrieval, celebrat l'1 d'abril de 2021 de manera virtual. | |
| dc.description.abstract | A related work report is a text which integrates key information from a list of related scientific papers providing context to the work being presented. In this paper we study the automatic generation of related work reports using extractive and abstractive text summarization approaches. Our extractive approach scores the sentences of the scientific papers based on their citations, selecting top scored sentences from each scientific paper to be mentioned in the related work report. The sentences are then organized in the report according to the topic they belong to. In additional experiments we use top scored sentences from our extractive methods and rephrase them using pre-trained abstractive models that generate citation sentences. We discuss automatic and manual evaluation of the generated related work reports showing the viability of the proposed approaches. | en |
| dc.description.sponsorship | This work was (partly) supported by the Spanish Government under the María de Maeztu Units of Excellence Programme (MDM-2015-0502). We also acknowledge support from the project Context-aware Multilingual Text Simplification (ConMuTeS) PID2019- 109066GB-I00/AEI/10.13039/501100011033 awarded by Ministerio de Ciencia, Innovación y Universidades (MCIU) and by Agencia Estatal de Investigación (AEI) of Spain. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | AbuRa’ed A, Saggion H. A select and rewrite approach to the generation of related work reports. In: Frommholz I, Mayr P, Cabanac G, Verberne S, editors. BIR 2021: 11th International Workshop on Bibliometric-enhanced Information Retrieval; 2021 Apr 1; Lucca, Italy. Aachen: CEUR; 2021. p. 53-68. | |
| dc.identifier.uri | http://hdl.handle.net/10230/47601 | |
| dc.language.iso | eng | |
| dc.publisher | CEUR Workshop Proceedings | |
| dc.relation.ispartof | Frommholz I, Mayr P, Cabanac G, Verberne S, editors. BIR 2021: 11th International Workshop on Bibliometric-enhanced Information Retrieval; 2021 Apr 1; Lucca, Italy. Aachen: CEUR; 2021. p. 53-68 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/ES/2PE/PID2019-109066GB-I00 | |
| dc.rights | Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0) | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.keyword | Scientific summarization | en |
| dc.subject.keyword | Information extraction from scientific literature | en |
| dc.subject.keyword | Document abstracting | en |
| dc.title | A select and rewrite approach to the generation of related work reports | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | info:eu-repo/semantics/publishedVersion |
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