Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information
The complex inner structures of concept names in the Foundational Model of Anatomy (FMA) remain an obstacle for further analyzing the ontology using lexical methods. A very common problem is the ambiguity lying in names with the sometimes multiple occurrences of the preposition “of.” In this paper...
| Main Authors: | , , |
|---|---|
| Format: | Online |
| Language: | English |
| Published: |
American Medical Informatics Association
201
|
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845762/ |
| id |
pubmed-3845762 |
|---|---|
| recordtype |
oai_dc |
| spelling |
pubmed-38457622013-12-03 Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information Luo, Lingyun Xu, Rong Zhang, Guo-Qiang Articles The complex inner structures of concept names in the Foundational Model of Anatomy (FMA) remain an obstacle for further analyzing the ontology using lexical methods. A very common problem is the ambiguity lying in names with the sometimes multiple occurrences of the preposition “of.” In this paper, we propose an automatic method to help disambiguating FMA terms by leveraging the taxonomy and partonomy information. If a sub-phrase of a concept name also appears in its parents, it is likely to occur as a sub-tree in its parse tree, hence should be parsed as such. We classified all the concept names with a single occurrence of the preposition “of” by the appearances of their sub-phrases in the parent names using three test suites. Results show that more than 90% of them can be provided with useful information to assist their correct parsing. American Medical Informatics Association 2013 -03- 18 /pmc/articles/PMC3845762/ /pubmed/24303256 Text en ©2013 AMIA - All rights reserved. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Luo, Lingyun Xu, Rong Zhang, Guo-Qiang |
| spellingShingle |
Luo, Lingyun Xu, Rong Zhang, Guo-Qiang Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information |
| author_facet |
Luo, Lingyun Xu, Rong Zhang, Guo-Qiang |
| author_sort |
Luo, Lingyun |
| title |
Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information
|
| title_short |
Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information
|
| title_full |
Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information
|
| title_fullStr |
Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information
|
| title_full_unstemmed |
Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information
|
| title_sort |
dissecting the ambiguity of fma concept names using taxonomy and partonomy structural information |
| description |
The complex inner structures of concept names in the Foundational Model of Anatomy (FMA) remain an obstacle for further analyzing the ontology using lexical methods. A very common problem is the ambiguity lying in names with the sometimes multiple occurrences of the preposition “of.” In this paper, we propose an automatic method to help disambiguating FMA terms by leveraging the taxonomy and partonomy information. If a sub-phrase of a concept name also appears in its parents, it is likely to occur as a sub-tree in its parse tree, hence should be parsed as such. We classified all the concept names with a single occurrence of the preposition “of” by the appearances of their sub-phrases in the parent names using three test suites. Results show that more than 90% of them can be provided with useful information to assist their correct parsing.
|
| publisher |
American Medical Informatics Association
|
| publishDate |
201 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845762/ |
| _version_ |
1612032409178472448 |