Presentation about my research given at the Manchester Institute of Biotechnology PhD symposium

1. Table mining and data
curation from biomedical
literature
Nikola Milosevic
Supervisors: Dr Goran Nenadic, Robert Hernandez

2. Why are we doing this?
 Growth of published research

3. Information growth

4. Text mining
 Text mining developed tools and
methods to help scientists
 Focused mainly on the body of the
article
 Tables and figures are typically
ignored

5. What about tables?

6. What about tables?

7. Challenge
 Visually structured text
 May be ungrammatical and
ambiguous
 Various layouts
 Value representation types
◦ Numeric
◦ Text
◦ Ranges
◦ Formulas
◦ Complex

8. Method overview

9. Method overview

10. Table decomposition
 Aim: Decompose table into the
structures suitable for further processing
 Cell structures that keep information
about navigational path (headers, stubs,
etc.)
 Heuristic based approach
 Cell structure, alignment, content,
neigbourhood

11. Table decomposition

12. Information extraction
 Performed a number of experiments
 Extraction of number of patients,
weight, BMI
 Approaches:
◦ Rules
◦ Metamap
◦ White and black lists

13. Results
 Achieved promising results
 Some of the information classes are
easier to extract than other

14. Conclusion & Future work
 Information extraction from tables is
feasible
 Future work:
◦ Value and table type categorisation
◦ Development of normalization and
extraction engine
◦ Extraction rules
◦ Data storing format (triple store, linked
data)
◦ Data curation interface
◦ Data querying interface

15. Thank you! Q&A
Email: nikola.milosevic@cs.man.ac.uk