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Entity resolution workflow installation process and user guide / Michael H. Lee.
Connect to full text Available online
View online- Format:
- Book
- Government document
- Author/Creator:
- Lee, Michael H., author.
- Language:
- English
- Subjects (All):
- Entity-relationship modeling.
- Data mining.
- Data Mining.
- Medical Subjects:
- Data Mining.
- Genre:
- Text
- Physical Description:
- 1 online resource (vi, 48 pages) : color illustrations
- Place of Publication:
- Adelphi, MD : Army Research Laboratory, July 2013.
- Language Note:
- English
- Summary:
- Entity resolution, in the context of text processing and information extraction domain, refers to the process of uniquely disambiguating a specific person or an object that appears in a text. For instance, if John Smith appears in a document, entity resolution seeks to identify who that John Smith specifically refers to from available choices in a database. This report describes the setup and configuration of the U.S. Army Research Laboratory s (ARL) software implementation of an entity resolution algorithm called Relationship-based Data Cleaning (RelDC), which systematically exploits not only features but also relationships among entities for the purpose of disambiguation. (The main concept is that) RelDC views the database as a graph of entities that are linked to each other via relationships. It first utilizes a feature-based method to identify a set of candidate entities (choices) for a reference to be disambiguated. Graph theoretic techniques are then used to discover and analyze relationships that exist between the entity containing the reference and the set of candidates. * In order to demonstrate the RelDC entity resolution algorithm in an intuitive and seamless way, ARL developed an Entity Resolution Workflow (ERW).
- Notes:
- "July 2013."
- "ARL-MR-0844."
- Approved for public release; distribution is unlimited.
- text/html
- Description based on online resource; title from PDF title page (ARL, viewed Oct. 4, 2019).
- OCLC:
- 872736669
- Access Restriction:
- Open access content Open access content
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