Knowledge-based personalized search engine for the Web-based Human Musculoskeletal System Resources (HMSR) in biomechanics

  • Authors:

  • Tien Tuan Dao;Tuan Nha Hoang;Xuan Hien Ta;Marie Christine Ho Ba Tho

  • Affiliations:

  • UTC CNRS UMR 7338, Biomécanique et Biongénierie (BMBI), Université de Technologie de Compiègne (UTC), BP 20529, 60205 Compiègne cedex, France;UTC CNRS UMR 7338, Biomécanique et Biongénierie (BMBI), Université de Technologie de Compiègne (UTC), BP 20529, 60205 Compiègne cedex, France;UTC CNRS UMR 7338, Biomécanique et Biongénierie (BMBI), Université de Technologie de Compiègne (UTC), BP 20529, 60205 Compiègne cedex, France;UTC CNRS UMR 7338, Biomécanique et Biongénierie (BMBI), Université de Technologie de Compiègne (UTC), BP 20529, 60205 Compiègne cedex, France

  • Venue:
  • Journal of Biomedical Informatics
  • Year:
  • 2013

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Abstract

Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical processes, pathological knowledge and practical expertise. In this present work, an advanced knowledge-based personalized search engine was developed. Our search engine was based on a client-server multi-layer multi-agent architecture and the principle of semantic web services to acquire dynamically accurate and reliable HMSR information by a semantic processing and visualization approach. A security-enhanced mechanism was applied to protect the medical information. A multi-agent crawler was implemented to develop a content-based database of HMSR information. A new semantic-based PageRank score with related mathematical formulas were also defined and implemented. As the results, semantic web service descriptions were presented in OWL, WSDL and OWL-S formats. Operational scenarios with related web-based interfaces for personal computers and mobile devices were presented and analyzed. Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized search engine. In fact, our knowledge-based personalized search engine allows different users such as orthopedic patient and experts or healthcare system managers or medical students to access remotely into useful, accurate, reliable and good-quality HMSR information for their learning and medical purposes.