Artikel

Developing an innovative entity extraction method for unstructured data

to connected objects

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.

Language
Englisch

Bibliographic citation
Journal: International Journal of Quality Innovation ; ISSN: 2363-7021 ; Volume: 3 ; Year: 2017 ; Issue: 3 ; Pages: 1-10 ; Heidelberg: Springer

Classification
Management
Subject
Entity extraction
Machine learning
Precision of extraction
Text analytics
Natural language processing

Event
Geistige Schöpfung
(who)
Zaghloul, Waleed
Trimi, Silvana
Event
Veröffentlichung
(who)
Springer
(where)
Heidelberg
(when)
2017

DOI
doi:10.1186/s40887-017-0012-y
Handle
Last update
10.03.2025, 11:41 AM CET

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Object type

  • Artikel

Associated

  • Zaghloul, Waleed
  • Trimi, Silvana
  • Springer

Time of origin

  • 2017

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