Details
| Original language | English |
|---|---|
| Title of host publication | Digital Libraries for Open Knowledge |
| Subtitle of host publication | 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, Proceedings |
| Editors | Mark Hall, Tanja Mercun, Thomas Risse, Fabien Duchateau |
| Place of Publication | Cham |
| Pages | 19-32 |
| Number of pages | 14 |
| ISBN (electronic) | 9783030549565 |
| Publication status | Published - 2020 |
| Event | 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020 - Lyon, France Duration: 25 Aug 2020 → 28 Aug 2020 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 12246 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Answering questions on scholarly knowledge comprising text and other artifacts is a vital part of any research life cycle. Querying scholarly knowledge and retrieving suitable answers is currently hardly possible due to the following primary reason: machine inactionable, ambiguous and unstructured content in publications. We present JarvisQA, a BERT based system to answer questions on tabular views of scholarly knowledge graphs. Such tables can be found in a variety of shapes in the scholarly literature (e.g., surveys, comparisons or results). Our system can retrieve direct answers to a variety of different questions asked on tabular data in articles. Furthermore, we present a preliminary dataset of related tables and a corresponding set of natural language questions. This dataset is used as a benchmark for our system and can be reused by others. Additionally, JarvisQA is evaluated on two datasets against other baselines and shows an improvement of two to three folds in performance compared to related methods.
Keywords
- Digital Libraries, Information retrieval, Question Answering, Scholarly knowledge, Semantic search, Semantic web
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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Digital Libraries for Open Knowledge: 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, Proceedings. ed. / Mark Hall; Tanja Mercun; Thomas Risse; Fabien Duchateau. Cham, 2020. p. 19-32 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12246 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Question Answering on Scholarly Knowledge Graphs
AU - Jaradeh, Mohamad Yaser
AU - Stocker, Markus
AU - Auer, Sören
N1 - Funding Information: This work was co-funded by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536) and the TIB Leibniz Information Centre for Science and Technology. The authors would like to thank our colleagues Kheir Eddine Farfar, Manuel Prinz, and especially Allard Oelen and Vitalis Wiens for their valuable input and comments.
PY - 2020
Y1 - 2020
N2 - Answering questions on scholarly knowledge comprising text and other artifacts is a vital part of any research life cycle. Querying scholarly knowledge and retrieving suitable answers is currently hardly possible due to the following primary reason: machine inactionable, ambiguous and unstructured content in publications. We present JarvisQA, a BERT based system to answer questions on tabular views of scholarly knowledge graphs. Such tables can be found in a variety of shapes in the scholarly literature (e.g., surveys, comparisons or results). Our system can retrieve direct answers to a variety of different questions asked on tabular data in articles. Furthermore, we present a preliminary dataset of related tables and a corresponding set of natural language questions. This dataset is used as a benchmark for our system and can be reused by others. Additionally, JarvisQA is evaluated on two datasets against other baselines and shows an improvement of two to three folds in performance compared to related methods.
AB - Answering questions on scholarly knowledge comprising text and other artifacts is a vital part of any research life cycle. Querying scholarly knowledge and retrieving suitable answers is currently hardly possible due to the following primary reason: machine inactionable, ambiguous and unstructured content in publications. We present JarvisQA, a BERT based system to answer questions on tabular views of scholarly knowledge graphs. Such tables can be found in a variety of shapes in the scholarly literature (e.g., surveys, comparisons or results). Our system can retrieve direct answers to a variety of different questions asked on tabular data in articles. Furthermore, we present a preliminary dataset of related tables and a corresponding set of natural language questions. This dataset is used as a benchmark for our system and can be reused by others. Additionally, JarvisQA is evaluated on two datasets against other baselines and shows an improvement of two to three folds in performance compared to related methods.
KW - Digital Libraries
KW - Information retrieval
KW - Question Answering
KW - Scholarly knowledge
KW - Semantic search
KW - Semantic web
UR - http://www.scopus.com/inward/record.url?scp=85090096407&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-54956-5_2
DO - 10.1007/978-3-030-54956-5_2
M3 - Conference contribution
AN - SCOPUS:85090096407
SN - 9783030549558
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 19
EP - 32
BT - Digital Libraries for Open Knowledge
A2 - Hall, Mark
A2 - Mercun, Tanja
A2 - Risse, Thomas
A2 - Duchateau, Fabien
CY - Cham
T2 - 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020
Y2 - 25 August 2020 through 28 August 2020
ER -