User-Customizable Health Pattern Detector Framework: Twitter Analysis Example | Zendy

Lianna Hall | Zendy; Kevin Nam | Zendy; Jason Thornton | Zendy; Marianne DeAngelus | Zendy; Timothy J. Dasey | Zendy

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User-Customizable Health Pattern Detector Framework: Twitter Analysis Example

Author(s) -

Lianna Hall,

Kevin Nam,

Jason Thornton,

Marianne DeAngelus,

Timothy J. Dasey

Publication year - 2015

Publication title -

online journal of public health informatics

Language(s) - English

Resource type - Journals

ISSN - 1947-2579

DOI - 10.5210/ojphi.v7i1.5798

Subject(s) - computer science , relevance (law) , business process reengineering , information retrieval , user interface , detector , extension (predicate logic) , relevance feedback , data mining , interface (matter) , term (time) , artificial intelligence , programming language , operating system , telecommunications , operations management , physics , quantum mechanics , lean manufacturing , political science , law , economics , bubble , maximum bubble pressure method , image (mathematics) , image retrieval

A general-purpose method for automatic detection algorithm reengineering based upon Twitter keyword queries using user relevance/irrelevance feedback has been demonstrated to have superior performance and versatility compared to more static detection methods. A demonstration of the capability with an initial user interface has been performed. An extension of the processing that includes initial query term expansion prior to application of the customized detection is being investigated.

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