Details
| Original language | English |
|---|---|
| Title of host publication | From Born-Physical to Born-Virtual |
| Subtitle of host publication | Augmenting Intelligence in Digital Libraries - 24th International Conference on Asian Digital Libraries, ICADL 2022, Proceedings |
| Editors | Yuen-Hsien Tseng, Marie Katsurai, Hoa N. Nguyen |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 290-300 |
| Number of pages | 11 |
| ISBN (print) | 9783031217555 |
| Publication status | Published - 7 Dec 2022 |
| Event | 24th International Conference on Asia-Pacific Digital Libraries, ICADL 2022 - Hanoi, Viet Nam Duration: 30 Nov 2022 → 2 Dec 2022 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 13636 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
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.
Keywords
- Information extraction, Literature review completion, Natural language processing, Scholarly knowledge, Summarization
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries - 24th International Conference on Asian Digital Libraries, ICADL 2022, Proceedings. ed. / Yuen-Hsien Tseng; Marie Katsurai; Hoa N. Nguyen. Springer Science and Business Media Deutschland GmbH, 2022. p. 290-300 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13636 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - MORTY
T2 - 24th International Conference on Asia-Pacific Digital Libraries, ICADL 2022
AU - Jaradeh, Mohamad Yaser
AU - Stocker, Markus
AU - Auer, Sören
PY - 2022/12/7
Y1 - 2022/12/7
N2 - 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.
AB - 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.
KW - Information extraction
KW - Literature review completion
KW - Natural language processing
KW - Scholarly knowledge
KW - Summarization
UR - http://www.scopus.com/inward/record.url?scp=85145008843&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2212.05429
DO - 10.48550/arXiv.2212.05429
M3 - Conference contribution
AN - SCOPUS:85145008843
SN - 9783031217555
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 290
EP - 300
BT - From Born-Physical to Born-Virtual
A2 - Tseng, Yuen-Hsien
A2 - Katsurai, Marie
A2 - Nguyen, Hoa N.
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 30 November 2022 through 2 December 2022
ER -