DocumentCode
3599449
Title
Tracing the Paths between Concepts in Large Bio-Medical Corpora
Author
Alaverdyan, Zaruhi ; Benedetti, Marcello ; Rabearison, Falitokiniaina ; Pathirana, Nishara ; Chiru, Costin-Gabriel ; Rebedea, Traian
Author_Institution
Univ. Lumiere Lyon 2, Lyon, France
fYear
2015
Firstpage
357
Lastpage
364
Abstract
Language suffers an everlasting process of change, both at a semantic level, where existing words acquire new meanings, and at a lexical level, where new concepts appear and old ones disappear or are used less frequently. New words (terms/concepts) may be added as a result of scientific discoveries or socio-cultural influences, while other words are "forgotten" or are assigned alternative meanings. These changes in a vocabulary usually characterize important shifts in the environment or the domain they are used in. For experts there is an evident connection between a new concept and some of the existing ones, but for regular people these relations remain hidden and need to be identified. In particular, in the medical domain new terms appear as a result of new discoveries and it becomes an important challenge to establish the connections between different concepts. Moreover, it is important to detect if such a relation even exists. In this paper, we present a graph-based approach to identify the semantic path (which is a chain of semantically related words) between the concepts that appeared in the bio-medicine publications available in the Pub Med corpus over a time period of 20 years.
Keywords
bioinformatics; graph theory; medical computing; natural language processing; nomenclature; text analysis; Pub Med corpus; bio-medical corpora; bio-medicine publications; concept path tracing; graph-based approach; lexical level; medical domain; scientific discovery; semantic path identification; semantically related words; socio-cultural influence; Arteries; Buildings; Elbow; Medical treatment; Semantics; Time series analysis; Vocabulary; Bio-medicine; Concept Tracing; Heuristic Search; Semantic Similarity; Text Mining; Time Series;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Systems and Computer Science (CSCS), 2015 20th International Conference on
Print_ISBN
978-1-4799-1779-2
Type
conf
DOI
10.1109/CSCS.2015.101
Filename
7168454
Link To Document