A systematic mapping study on open information extraction. (1st December 2018)
- Record Type:
- Journal Article
- Title:
- A systematic mapping study on open information extraction. (1st December 2018)
- Main Title:
- A systematic mapping study on open information extraction
- Authors:
- Glauber, Rafael
Barreiro Claro, Daniela - Abstract:
- Highlights: To the best of our knowledge, this is the first systematic mapping on open information extraction. We provide a systematic organization of published papers on open information extraction area. We define some principles about OpenIE systems to help new researchers on knowing this growing area. We discuss open problems and current trends of open information extraction area. Abstract: Open information extraction (Open IE) is a task for extracting relationship triples in plain texts without previously determining these relationships. The Open IE systems are generally applied to solutions on the web-scale such improving question answering systems, ontology constructions, document filtering and clustering. Since 2007, within the first Open IE system TEXTRUNNER, other related works have been proposed in this area. Despite other secondary studies on Open IE, useful information available to initiate new research in the area is limited. Thus, we propose a review of the literature in Open IE by a systematic mapping study. We have retrieved 2484 articles about Open IE in Science Direct, IEEE Xplore, ACM Digital Library, Scopus and Google Scholar databases. Among them, 2411 were filtered by exclusion criteria proposed in our systematic mapping protocol. The remaining 73 papers represent the state-of-the-art from the past seven years. Different researchers have proposed important contributions and have pointed out some open problems for Open IE. As a result, we summarizedHighlights: To the best of our knowledge, this is the first systematic mapping on open information extraction. We provide a systematic organization of published papers on open information extraction area. We define some principles about OpenIE systems to help new researchers on knowing this growing area. We discuss open problems and current trends of open information extraction area. Abstract: Open information extraction (Open IE) is a task for extracting relationship triples in plain texts without previously determining these relationships. The Open IE systems are generally applied to solutions on the web-scale such improving question answering systems, ontology constructions, document filtering and clustering. Since 2007, within the first Open IE system TEXTRUNNER, other related works have been proposed in this area. Despite other secondary studies on Open IE, useful information available to initiate new research in the area is limited. Thus, we propose a review of the literature in Open IE by a systematic mapping study. We have retrieved 2484 articles about Open IE in Science Direct, IEEE Xplore, ACM Digital Library, Scopus and Google Scholar databases. Among them, 2411 were filtered by exclusion criteria proposed in our systematic mapping protocol. The remaining 73 papers represent the state-of-the-art from the past seven years. Different researchers have proposed important contributions and have pointed out some open problems for Open IE. As a result, we summarized these contributions and identified significant gaps that could be envisioned as future works. … (more)
- Is Part Of:
- Expert systems with applications. Volume 112(2018)
- Journal:
- Expert systems with applications
- Issue:
- Volume 112(2018)
- Issue Display:
- Volume 112, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 112
- Issue:
- 2018
- Issue Sort Value:
- 2018-0112-2018-0000
- Page Start:
- 372
- Page End:
- 387
- Publication Date:
- 2018-12-01
- Subjects:
- Systematic mapping study -- Open information extraction -- Open relation extraction -- Open knowledge acquisition -- Open relation mapping
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2018.06.046 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7159.xml