Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | SEMANTiCS-Workshops 2023 |
| Untertitel | SEMANTiCS Workshops Proceedings Compound Volume 2023 |
| Seitenumfang | 12 |
| Publikationsstatus | Veröffentlicht - 17 Okt. 2023 |
| Veranstaltung | 5th Sem4Tra Workshop, and 2nd NLP4KGC Workshop co-located with SEMANTiCS 2023 - Hybrid, Leipzig, Deutschland Dauer: 20 Sept. 2023 → 20 Sept. 2023 |
Publikationsreihe
| Name | CEUR Workshop Proceedings |
|---|---|
| Herausgeber (Verlag) | CEUR Workshop Proceedings |
| Band | 3510 |
| ISSN (Print) | 1613-0073 |
Abstract
This paper outlines the core features and implementation details of the Similar Papers Recommendation service, which aims to expedite the creation and expansion of research paper comparisons within the Open Research Knowledge Graph (ORKG). By leveraging Semantic Scholar’s Recommendations API and Elastic Search, the service provides a list of similar papers for a given comparison, considering both paper titles, abstracts, and their property values. The use of Semantic Scholar’s Recommendations API allows the service to capitalize on machine learning techniques and semantic embeddings to generate relevant and tailored recommendations. The effectiveness of the service is demonstrated through the evaluation results, highlighting its potential as a valuable resource for the research community within the ORKG platform.
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SEMANTiCS-Workshops 2023: SEMANTiCS Workshops Proceedings Compound Volume 2023. 2023. (CEUR Workshop Proceedings; Band 3510).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Similar Papers Recommendation for Research Comparisons
AU - Nechakhin, Vladyslav
AU - D’Souza, Jennifer
PY - 2023/10/17
Y1 - 2023/10/17
N2 - This paper outlines the core features and implementation details of the Similar Papers Recommendation service, which aims to expedite the creation and expansion of research paper comparisons within the Open Research Knowledge Graph (ORKG). By leveraging Semantic Scholar’s Recommendations API and Elastic Search, the service provides a list of similar papers for a given comparison, considering both paper titles, abstracts, and their property values. The use of Semantic Scholar’s Recommendations API allows the service to capitalize on machine learning techniques and semantic embeddings to generate relevant and tailored recommendations. The effectiveness of the service is demonstrated through the evaluation results, highlighting its potential as a valuable resource for the research community within the ORKG platform.
AB - This paper outlines the core features and implementation details of the Similar Papers Recommendation service, which aims to expedite the creation and expansion of research paper comparisons within the Open Research Knowledge Graph (ORKG). By leveraging Semantic Scholar’s Recommendations API and Elastic Search, the service provides a list of similar papers for a given comparison, considering both paper titles, abstracts, and their property values. The use of Semantic Scholar’s Recommendations API allows the service to capitalize on machine learning techniques and semantic embeddings to generate relevant and tailored recommendations. The effectiveness of the service is demonstrated through the evaluation results, highlighting its potential as a valuable resource for the research community within the ORKG platform.
UR - http://www.scopus.com/inward/record.url?scp=85175660133&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85175660133
T3 - CEUR Workshop Proceedings
BT - SEMANTiCS-Workshops 2023
T2 - 5th Sem4Tra Workshop, and 2nd NLP4KGC Workshop co-located with SEMANTiCS 2023
Y2 - 20 September 2023 through 20 September 2023
ER -