Case Representation and Retrieval Techniques for Neuroanatomical Connectivity Extraction from PubMed

  • Ashika Sharma
  • Ankit Sharma
  • Dipti Deodhare
  • Sutanu Chakraborti
  • P. Sreenivasa Kumar
  • P. Partha Mitra
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9969)

Abstract

PubMed is a comprehensive database of abstracts and references of a large number of publications in the biomedical domain. Curation of structured connectivity databases creates an easy access point to the wealth of neuroanatomical connectivity information reported in the literature over years. Manual curation of such databases is time consuming and labor intensive. We present a Case Based Reasoning (CBR) approach to automatically compile connectivity status between brain region mentions in text. We focus on the Case Retrieval part of the CBR cycle and present three Instance based learning techniques to retrieve similar cases from the case base. These techniques use varied case representations ranging from surface level features to richer syntax based features. We have experimented with diverse similarity measures and feature weighting schemes for each technique. The three techniques have been evaluated and compared using a benchmark dataset from PubMed and it was found that the one using deep syntactic features gives the best trade off between Precision and Recall. In this study, we have explored issues pertaining to representation of, and retrieval over textual cases. It is envisaged that the ideas presented in the paper can be adapted to needs of other textual CBR domains as well.

Keywords

Case representation Case retrieval Connectivity extraction Instance based learning 

References

  1. 1.
    Agichtein, E., Gravano, L.: Snowball: extracting relations from large plain-text collections. In: Proceedings of the Fifth ACM Conference on Digital Libraries, pp. 85–94. ACM (2000)Google Scholar
  2. 2.
    Connectome of Rat cerebrum from Brain Architecture Management System (BAMS). https://bams2.bams1.org/connections/grid/80/
  3. 3.
    Frakes, W.B., Baeza-Yates, R.: Information Retrieval: Data Structures and Algorithms. Prentice-Hall, Englewood Cliffs (1992)Google Scholar
  4. 4.
    French, L., Liu, P., Marais, O., Koreman, T., Tseng, L., Lai, A., Pavlidis, P.: Text mining for neuroanatomy using WhiteText with an updated corpus and a new web application. Front. Neuroinformatics 9, 13 (2015). doi:10.3389/fninf.2015.00013. ISSN: 1662–5196CrossRefGoogle Scholar
  5. 5.
    Jurafsky, D.: Speech and Language Processing. Pearson Education, India (2000)Google Scholar
  6. 6.
    Kluegl, P., Toepfer, M., Beck, P.D., Fette, G., Puppe, F.: UIMA Ruta: Rapid development of rule-based information extraction applications. Nat. Lang. Eng. 1(1), 1–40 (2014)Google Scholar
  7. 7.
    Link Grammar Parser. http://www.link.cs.cmu.edu/link/
  8. 8.
    Michalski, R.S., Carbonell, J.G., Mitchell, T.M. (eds.): Machine Learning: An Artificial Intelligence Approach. Springer, Heidelberg (2013)Google Scholar
  9. 9.
    Richardet, R., Chappelier, J.C., Telefont, M., Hill, S.: Large-scale extraction of brain connectivity from the neuroscientific literature. Bioinformatics 31(10), 1640–1647 (2015)CrossRefGoogle Scholar
  10. 10.
    Sleator, D.D., Temperley, D.: Parsing English with a link grammar. arXiv preprint (1995)Google Scholar
  11. 11.
    Suchanek, F.M., Ifrim, G., Weikum, G.: LEILA: Learning to extract information by linguistic analysis. In: Proceedings of the 2nd Workshop on Ontology Learning and Population: Bridging the Gap Between Text and Knowledge, pp. 18–25 (2006)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Ashika Sharma
    • 1
    • 2
  • Ankit Sharma
    • 1
  • Dipti Deodhare
    • 2
  • Sutanu Chakraborti
    • 1
  • P. Sreenivasa Kumar
    • 1
  • P. Partha Mitra
    • 3
  1. 1.Department of Computer ScienceIndian Institute of Technology MadrasChennaiIndia
  2. 2.Center for Artificial Intelligence and RoboticsDRDOBangaloreIndia
  3. 3.Cold Spring Harbor LabsNew YorkUSA

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