scholarly journals COMPARISON SEMANTIC SIMILARITY APPROACH USING BIOMEDICAL DOMAIN DATASET

2017 ◽  
Vol 1 (2) ◽  
pp. 01-04 ◽  
Author(s):  
Shahreen Kasim ◽  
Nurul Aswa Omar ◽  
Nurul Suhaida Mohammad Akbar ◽  
Rohayanti Hassan ◽  
Marzanah A. Jabar
Keyword(s):  
Semantic Similarity ◽  
Biomedical Domain

scholarly journals A framework for unifying ontology-based semantic similarity measures: A study in the biomedical domain

2014 ◽  
Vol 48 ◽  
pp. 38-53 ◽  
Author(s):  
Sébastien Harispe ◽  
David Sánchez ◽  
Sylvie Ranwez ◽  
Stefan Janaqi ◽  
Jacky Montmain
Keyword(s):  
Semantic Similarity ◽  
Similarity Measures ◽  
Biomedical Domain

scholarly journals HESML: a real-time semantic measures library for the biomedical domain with a reproducible survey

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Juan J. Lastra-Díaz ◽  
Alicia Lara-Clares ◽  
Ana Garcia-Serrano
Keyword(s):  
Real Time ◽  
Semantic Similarity ◽  
Similarity Measure ◽  
Shortest Path ◽  
State Of The Art ◽  
Biomedical Domain ◽  
Snomed Ct ◽  
Shortest Path Algorithm ◽  
Semantic Similarity Measure ◽  
Current State

Abstract Background Ontology-based semantic similarity measures based on SNOMED-CT, MeSH, and Gene Ontology are being extensively used in many applications in biomedical text mining and genomics respectively, which has encouraged the development of semantic measures libraries based on the aforementioned ontologies. However, current state-of-the-art semantic measures libraries have some performance and scalability drawbacks derived from their ontology representations based on relational databases, or naive in-memory graph representations. Likewise, a recent reproducible survey on word similarity shows that one hybrid IC-based measure which integrates a shortest-path computation sets the state of the art in the family of ontology-based semantic measures. However, the lack of an efficient shortest-path algorithm for their real-time computation prevents both their practical use in any application and the use of any other path-based semantic similarity measure. Results To bridge the two aforementioned gaps, this work introduces for the first time an updated version of the HESML Java software library especially designed for the biomedical domain, which implements the most efficient and scalable ontology representation reported in the literature, together with a new method for the approximation of the Dijkstra’s algorithm for taxonomies, called Ancestors-based Shortest-Path Length (AncSPL), which allows the real-time computation of any path-based semantic similarity measure. Conclusions We introduce a set of reproducible benchmarks showing that HESML outperforms by several orders of magnitude the current state-of-the-art libraries in the three aforementioned biomedical ontologies, as well as the real-time performance and approximation quality of the new AncSPL shortest-path algorithm. Likewise, we show that AncSPL linearly scales regarding the dimension of the common ancestor subgraph regardless of the ontology size. Path-based measures based on the new AncSPL algorithm are up to six orders of magnitude faster than their exact implementation in large ontologies like SNOMED-CT and GO. Finally, we provide a detailed reproducibility protocol and dataset as supplementary material to allow the exact replication of all our experiments and results.

scholarly journals Neural sentence embedding models for semantic similarity estimation in the biomedical domain

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Kathrin Blagec ◽  
Hong Xu ◽  
Asan Agibetov ◽  
Matthias Samwald
Keyword(s):  
Semantic Similarity ◽  
Biomedical Domain ◽  
Similarity Estimation

Semantic Similarity Measures in the Biomedical Domain by Leveraging a Web Search Engine

2013 ◽  
Vol 17 (4) ◽  
pp. 853-861 ◽  
Author(s):  
Sheau-Ling Hsieh ◽  
Wen-Yung Chang ◽  
Chi-Huang Chen ◽  
Yung-Ching Weng
Keyword(s):  
Semantic Similarity ◽  
Search Engine ◽  
Web Search ◽  
Similarity Measures ◽  
Biomedical Domain ◽  
Web Search Engine
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