Developing an innovative entity extraction method for unstructured data
Waleed Zaghloul () and
Silvana Trimi ()
Additional contact information
Waleed Zaghloul: Valera Intelligent Systems
Silvana Trimi: University of Nebraska
International Journal of Quality Innovation, 2017, vol. 3, issue 1, 1-10
Abstract The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and applications. The improvement of entities extraction precision also increases the relationships extraction precision, which is particularly important in certain domains (such as intelligence systems, social networking, genetic studies, healthcare, etc.). These increases in precision improve the end users’ experience quality in using the extraction system because it lowers the time that users spend for training the system and correcting outputs, focusing more on analyzing the information extracted to make better data-driven decisions.
Keywords: Entity extraction; Machine learning; Precision of extraction; Text analytics; Natural language processing (search for similar items in EconPapers)
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1186/s40887-017-0012-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:spr:ijoqin:v:3:y:2017:i:1:d:10.1186_s40887-017-0012-y
Ordering information: This journal article can be ordered from
Access Statistics for this article
International Journal of Quality Innovation is currently edited by Sang M. Lee
More articles in International Journal of Quality Innovation from Springer
Bibliographic data for series maintained by Sonal Shukla ().