A Bidirectional-Based Spreading Activation Method for Human Diseases Relatedness Detection Using Disease Ontology

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10448)

Abstract

There is a numerous demand for a standard representation of the ubiquitous available information on the web. Developing an efficient algorithm for traversing large ontologies is a key challenge for many semantic web applications. This paper proposes spreading activation over ontology method based on bidirectional search technique in order to detect the relatedness between two human diseases. The aim of our work is to detect disease relatedness by considering semantic domain knowledge and description logic rules to identify diseases relatedness. The proposed method is divided into two phases: Semantic Matching and Disease Relatedness Detection. In Semantic matching phase, diseases in submitted query are semantically identified in the ontology graph. In Disease relatedness detection phase, disease relatedness is detected by running a bidirectional-based spreading activation algorithm and return the related path (set of diseases) if so. In addition, the classification of these diseases is provided as well.

Keywords

Bidirectional search Disease ontology Semantic web Spreading activation 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Enterprise Information Systems (EIS)University of BonnBonnGermany
  2. 2.Faculty of ScienceAlexandria UniversityAlexandriaEgypt
  3. 3.Software EngineerAlexandriaEgypt

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