Details
| Original language | English |
|---|---|
| Title of host publication | The Semantic Web |
| Subtitle of host publication | ESWC 2017 Satellite Events - Revised Selected Papers |
| Editors | Eva Blomqvist, Olaf Hartig, Heiko Paulheim, Katja Hose, Fabio Ciravegna, Agnieszka Lawrynowicz |
| Publisher | Springer Verlag |
| Pages | 12-16 |
| Number of pages | 5 |
| ISBN (print) | 9783319704067 |
| Publication status | Published - 2017 |
| Event | 14th International Conference on Semantic Web, ESWC 2017 - Portoroz, Slovenia Duration: 28 May 2017 → 1 Jun 2017 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10577 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
We explore methods to extract relations between named entities from free text in an unsupervised setting. In addition to standard feature extraction, we develop a novel method to re-weight word embeddings. We alleviate the problem of features sparsity using an individual feature reduction. Our approach exhibits a significant improvement by 5.8% over the state-of-the-art relation clustering scoring a F1-score of 0.416 on the NYT-FB dataset.
Keywords
- NLP, Relation extraction, Word embedding
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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The Semantic Web: ESWC 2017 Satellite Events - Revised Selected Papers. ed. / Eva Blomqvist; Olaf Hartig; Heiko Paulheim; Katja Hose; Fabio Ciravegna; Agnieszka Lawrynowicz. Springer Verlag, 2017. p. 12-16 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10577 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Unsupervised Open Relation Extraction
AU - Elsahar, Hady
AU - Demidova, Elena
AU - Gottschalk, Simon
AU - Gravier, Christophe
AU - Laforest, Frederique
N1 - Publisher Copyright: © Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - We explore methods to extract relations between named entities from free text in an unsupervised setting. In addition to standard feature extraction, we develop a novel method to re-weight word embeddings. We alleviate the problem of features sparsity using an individual feature reduction. Our approach exhibits a significant improvement by 5.8% over the state-of-the-art relation clustering scoring a F1-score of 0.416 on the NYT-FB dataset.
AB - We explore methods to extract relations between named entities from free text in an unsupervised setting. In addition to standard feature extraction, we develop a novel method to re-weight word embeddings. We alleviate the problem of features sparsity using an individual feature reduction. Our approach exhibits a significant improvement by 5.8% over the state-of-the-art relation clustering scoring a F1-score of 0.416 on the NYT-FB dataset.
KW - NLP
KW - Relation extraction
KW - Word embedding
UR - http://www.scopus.com/inward/record.url?scp=85034246778&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-70407-4_3
DO - 10.1007/978-3-319-70407-4_3
M3 - Conference contribution
AN - SCOPUS:85034246778
SN - 9783319704067
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 12
EP - 16
BT - The Semantic Web
A2 - Blomqvist, Eva
A2 - Hartig, Olaf
A2 - Paulheim, Heiko
A2 - Hose, Katja
A2 - Ciravegna, Fabio
A2 - Lawrynowicz, Agnieszka
PB - Springer Verlag
T2 - 14th International Conference on Semantic Web, ESWC 2017
Y2 - 28 May 2017 through 1 June 2017
ER -