Full metadata
Title
Context-aware adaptive hybrid semantic relatedness in biomedical science
Description
Text mining of biomedical literature and clinical notes is a very active field of research in biomedical science. Semantic analysis is one of the core modules for different Natural Language Processing (NLP) solutions. Methods for calculating semantic relatedness of two concepts can be very useful in solutions solving different problems such as relationship extraction, ontology creation and question / answering [1–6]. Several techniques exist in calculating semantic relatedness of two concepts. These techniques utilize different knowledge sources and corpora. So far, researchers attempted to find the best hybrid method for each domain by combining semantic relatedness techniques and data sources manually. In this work, attempts were made to eliminate the needs for manually combining semantic relatedness methods targeting any new contexts or resources through proposing an automated method, which attempted to find the best combination of semantic relatedness techniques and resources to achieve the best semantic relatedness score in every context. This may help the research community find the best hybrid method for each context considering the available algorithms and resources.
Date Created
2016
Contributors
- Emadzadeh, Ehsan (Author)
- Gonzalez, Graciela (Thesis advisor)
- Greenes, Robert (Committee member)
- Scotch, Matthew (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
x, 83 pages : color illustrations
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.38725
Statement of Responsibility
by Ehsan Emadzadeh
Description Source
Viewed on August 4, 2016
Level of coding
full
Note
Partial requirement for: Ph.D., Arizona State University, 2016
Note type
thesis
Includes bibliographical references (pages 75-83)
Note type
bibliography
Field of study: Biomedical informatics
System Created
- 2016-06-01 08:58:29
System Modified
- 2021-08-30 01:22:55
- 2 years 8 months ago
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