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Proceedings of the Second International Conference on Computer and Communication Technologies pp 449–461Cite as

Semantic-Based Approach for Automatic Annotation and Classification of Medical Services in Healthcare Ecosystem

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 379))

Abstract

A vast amount of related healthcare information exists over the web without any explicit semantic association. Healthcare ecosystem makes use of medical services for the services entities of publishing and classification. However, before the emergence of healthcare ecosystems, where ecosystems are generally present in the environment, medical service and healthcare information are diverse. Therefore, the first medical service is a key issue to deal with information systems in the healthcare environment. In this paper, we propose health-related clinical data annotation, classification, and interpretation of medical data in relation to the level of classification based on the existence of the frame, and for improving the customer’s request to present a semantic-based Web mining. In addition, we classify medical data in relation to the level of clustering based on the use of healthcare information. Information relevant to the development of semantic information extraction can be achieved using a better phrase. Highly relevant improved information requested can be retrieved by deployment of additional medical terms. Our experimental evaluation results and the feasibility of assessing the impact of the proposed mining method show improvisation.

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References

  1. Winn, J., Bishop, C.: A Unified Modeling Approach to Data Intensive Healthcare. Health And Wellbeing, Microsoft Research (2007)

    Google Scholar 

  2. Li, J., Zhang, Z., Li, X., Chen, H.: Kernel-based learning for biomedical relation extraction. J. Am. Soc. Info. Sci. Technol. 59(5), 756–769 (2008)

    Article  MathSciNet  Google Scholar 

  3. Yakushiji, A., Tateisi, Y., Miyao, Y., Tsujii, J.: Event extraction from biomedical papers using a full parser. Proc. Pacific Symp. Biocomput. 6, 408–419 (2001)

    Google Scholar 

  4. Donaldson, I., et al.: PreBIND and Textomy: mining the biomedical literature for Protein-Protein interactions using a support vector machine. BMC Bioinf. 4 (2003)

    Google Scholar 

  5. Srinivasan, P., Rindflesch, T.: Exploring text mining from medline. In: Proceedings of the American Medical Informatics Association (AMIA) Symposium, pp. 722–726 (2002)

    Google Scholar 

  6. Pustejovsky, J., Castan’o, J., Zhang, M.K., Cochran, B.: Robust relational parsing over biomedical literature: extracting inhibit relations. Proc. Pacific Symp. Biocomput. 7, 362–373 (2002)

    Google Scholar 

  7. Lastra, J.L.M., Delamer, M.: Semantic web services in factory automation: fundamental insights and research roadmap. IEEE Tran. 2(1), 1–11 (2006)

    Google Scholar 

  8. Dong, H., Hussain, F.K., Chang, E.: State of the art in semantic focused crawlers. In: International Conference on ICCSA, pp. 890–904. Yongin, Korea (2009)

    Google Scholar 

  9. Johnson H.L., Cohen K.B., Baumgartner, W.A., et al.: Evaluation of lexical methods for detecting relationships between concepts from multiple ontologies. Proc. Pacific Symp. Biocomput. (2006)

    Google Scholar 

  10. Frunza, O., Inkpen, D., Thomas, T.: A machine learning approach for identifying disease treatment relations in short texts. IEEE Trans. Knowl. Data Eng. 23(6), 801–814 (2011)

    Article  Google Scholar 

  11. Thomas, J., Milward, D., Ouzounis, C., Pulman, S., Carroll, M.: Automatic extraction of protein interations from scientific abstracts. Proc. Pacific Symp. Biocomput. 5, 538–549 (2000)

    Google Scholar 

  12. Hunter, L., Cohen, K.B.: Biomedical language processing: what’s beyond PubMed? Mol. Cell 21–5, 589–594 (2006)

    Article  Google Scholar 

  13. Ganesh, S., Jayaraj, M., Kalyan, V., Aghila, G.: Ontology-based web crawler. In: Proceedings of the ITCC: Coding Computing, pp. 337–341. Las Vegas, NV (2004)

    Google Scholar 

  14. Hunter, L., Lu, Z., et al: OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression. BMC Bioinf. 9(78) (2008)

    Google Scholar 

  15. Dong, H., Hussain, F.K., Chang, E.: A survey in semantic web technologies inspired focused crawlers. In: 3rd International Conference of ICDIM, pp. 934–936. East London, UK (2008)

    Google Scholar 

  16. Rosario, B., Hearst, M.A.: Semantic relations in bioscience text. In: 42nd—Annual Meeting on Association for Computational Linguistics, vol. 430 (2004)

    Google Scholar 

  17. Ray, S., Craven, M.: Representing sentence structure in hidden Markov models for information extraction. Int. J. CAI (2001)

    Google Scholar 

  18. Yuvarani, M., Iyengar, N.C.S.N., Kannan, A.: LSCrawler: a framework for an enhanced focused web crawler based on link semantics. In: Proceedings of the IEEE/WIC/ACM International Conference WI, pp. 794–800 (2006)

    Google Scholar 

  19. Antonie, M.L., Zaane, O.R.: Text document categorization by term association. In: Proceedings of the IEEE International Conference Data Mining (ICDM ’02) (2002)

    Google Scholar 

  20. Tane, J., Schmitz, C., Stumme, G.: Semantic resource management for the web: an e-learning application. In: WWW 2004, pp. 1–10. ACM, New York (2004)

    Google Scholar 

  21. Heb, A., Kushmerick, N.: Automatically attaching semantic metadata to web services. In: Procceding IJCAI Workshop Information Integration on the Web (2003)

    Google Scholar 

  22. Francesconi, E., Peruginelli, G.: Searching and retrieving legal literature through automated semantic indexing, pp. 131–138. ICAIL, Standford, CA (2007)

    Google Scholar 

  23. Giles, C.L., Petinot, Y., et al.: e-BizSearch: a niche search engine for e-business. In: Proceeding for SIGIR, pp. 413–414. Toronto, ON, Canada (2003)

    Google Scholar 

  24. Bruno, M., Canfora, G., Penta M.D., Scognamiglio, R.: An approach to support web service classification and annotation. In: Proceeding IEEE International Conference. E-Tech, E-Comm and E-Service (EEE-05) (2005)

    Google Scholar 

  25. Halkidi, M., Varlamis, N.B., Vazirgiannis, M.: THESUS: Organizing web document collections based on link semantics. VLDB J. 12(4), 320–332 (2003)

    Article  Google Scholar 

  26. Klusch, M., Zhing, X.: Deployed semantic services for the common user of the web: a reality check. In: Proceeding for IEEE International Semantic Computing (ICSC) (2008)

    Google Scholar 

  27. Leroy, G., Chen, H.C., Martinez, J.D.: A shallow parser based on closed-class words to capture relations in biomedical text. J. Biomed. Inform. 36(3), 145–158 (2003)

    Article  Google Scholar 

  28. Giuliano, C., Alberto, L., Lorenza, R.: Exploiting shallow linguistic information for relation extraction from biomedical literature. In: Proceedings of the 11th Conference European Chapter of the Association for Computational Linguistics (2006)

    Google Scholar 

  29. Xiong H., Tan, P., Kumar, V.: Mining strong affinity association patterns in data sets with skewed support distribution. In: Proceeding for IEEE Third International Conference of Data Mining (2003)

    Google Scholar 

  30. Goadrich, M., Oliphant, L., Shavlik, J.: Learning ensembles of first-order clauses for recall-precision curves: a case study in biomedical information extraction. In: Proceedings of the 14th International Conference (2004)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of CSE, Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Hyderabad, India

    Vijayalakshmi Kakulapati, Rishi Sayal & Ravi Aavula

  2. Department of CSE, C.M.R Institute of Technology, Kondlakoya, Hyderabad, India

    Sunitha Devi Bigul

Authors
  1. Vijayalakshmi Kakulapati
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  2. Rishi Sayal
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  3. Ravi Aavula
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  4. Sunitha Devi Bigul
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Corresponding author

Correspondence to Vijayalakshmi Kakulapati .

Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

  2. Department of CSE, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

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Kakulapati, V., Sayal, R., Aavula, R., Bigul, S.D. (2016). Semantic-Based Approach for Automatic Annotation and Classification of Medical Services in Healthcare Ecosystem. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 379. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2517-1_43

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  • DOI: https://doi.org/10.1007/978-81-322-2517-1_43

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2516-4

  • Online ISBN: 978-81-322-2517-1

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