Tracing the Paths between Concepts in Large Bio-Medical Corpora

• Published in: 2015 20th International Conference on Control Systems and Computer Science pp. 357 - 364
• Main Authors: Alaverdyan, Zaruhi, Benedetti, Marcello, Rabearison, Falitokiniaina, Pathirana, Nishara, Chiru, Costin-Gabriel, Rebedea, Traian
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2015
• Subjects: Arteries; Bio-medicine; Buildings; Concept Tracing; Elbow; Heuristic Search; Medical treatment; Semantic Similarity; Semantics; Text Mining; Time Series; Time series analysis; Vocabulary
• ISSN: 2379-0474
• DOI: 10.1109/CSCS.2015.101

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.