Jaradeh, M.Y.; Stocker, M.; Auer, S.: MORTY: Structured Summarization for Targeted Information Extraction from Scholarly Articles. In: Tseng, YH.; Katsurai, M.; Nguyen, H.N. (Eds.): From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. New York, NY : Springer, 2022 (Lecture notes in computer science ; 13636), S. 290-300. DOI:
https://doi.org/10.1007/978-3-031-21756-2_23
Zusammenfassung: |
Information extraction from scholarly articles is a challenging task due to the sizable document length and implicit information hidden in text, figures, and citations. Scholarly information extraction has various applications in exploration, archival, and curation services for digital libraries and knowledge management systems. We present MORTY, an information extraction technique that creates structured summaries of text from scholarly articles. Our approach condenses the article’s full-text to property-value pairs as a segmented text snippet called structured summary. We also present a sizable scholarly dataset combining structured summaries retrieved from a scholarly knowledge graph and corresponding publicly available scientific articles, which we openly publish as a resource for the research community. Our results show that structured summarization is a suitable approach for targeted information extraction that complements other commonly used methods such as question answering and named entity recognition.
|
Lizenzbestimmungen: |
This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed on other websites via the internet or passed on to external parties. |
Publikationstyp: |
BookPart |
Publikationsstatus: |
acceptedVersion |
Erstveröffentlichung: |
2022 |
Schlagwörter (englisch): |
Information extraction, Literature review completion, Natural language processing, Scholarly knowledge, Summarization
|
Fachliche Zuordnung (DDC): |
620 | Ingenieurwissenschaften und Maschinenbau
|
Kontrollierte Schlagwörter: |
Konferenzschrift
|