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1 © University Hospitals of Geneva Division of Medical Information Sciences
AN ADVANCED SEARCH ENGINE FOR PATENT ANALYTICS IN MEDICINAL CHEMISTRY
Emilie Pasche1, Julien Gobeill2, Douglas Teodoro1, Arnaud Gaudinat2, Dina Vishnyakova1,
ChrisKan Lovis1, Patrick Ruch2
1SIMED, University and University Hospitals of Geneva 2BiTeM, University of Applied Sciences, Geneva
2 © University Hospitals of Geneva Division of Medical Information Sciences
Plan
1. Introduc+on
2. Methods
3. Results
4. Demo
5. Conclusion
3 © University Hospitals of Geneva Division of Medical Information Sciences
IntroducKon
Our objec+ve Development of TWINC, a web interface to search medical-‐related patents. What is the interest of patent collec+ons? • Unique and validated informaKon • Source of knowledge for biomedicine
• 460’000 patents related to biomedicine from 2005 to 2009
4 © University Hospitals of Geneva Division of Medical Information Sciences
IntroducKon
What is the problem? Currents tools are limited • Lack of useful funcKonaliKes • Naming ambiguity
What are the solu+ons? InformaKon retrieval campaigns to foster the research • Text Retrieval Conferences (TREC) • PatOlympics
5 © University Hospitals of Geneva Division of Medical Information Sciences
Plan
1. IntroducKon
2. Methods
3. Results
4. Demo
5. Conclusion
6 © University Hospitals of Geneva Division of Medical Information Sciences
Methods: Overview
TWINC features:
Search modes: • Ad hoc search • Related patent search
AddiKonal funcKonaliKes: • Chemical query expansion • AutomaKc IPC classificaKon • Rocchio-‐based query refinement
7 © University Hospitals of Geneva Division of Medical Information Sciences
Methods: Search modes
General methodology
Ad hoc search • Retrieve a set of relevant documents
• Short query
Related patent search • Retrieve a set of similar documents
• Long query
8 © University Hospitals of Geneva Division of Medical Information Sciences
Methods: AddiKonal funcKonaliKes
Chemical Query Expansion • Different communiKes have different ways of naming enKKes
• Physicians will prefer brand names • Chemists will prefer chemical names • Biologists will prefer substance names
Methodology
Query Chemical
idenKficaKon Chemical
normalizaKon Synonyms expansion
9 © University Hospitals of Geneva Division of Medical Information Sciences
Methods: EvaluaKon
Quan+ta+ve evalua+on • Ad hoc search
• 6 short topics provided by TREC • Related patent search
• 1000 long topics provided by TREC
Qualita+ve evalua+on • User interface
• 3 experts perform each a different query
10 © University Hospitals of Geneva Division of Medical Information Sciences
Plan
1. IntroducKon
2. Methods
3. Results
4. Demo
5. Conclusion
11 © University Hospitals of Geneva Division of Medical Information Sciences
Results: Search modes
Ad hoc search
• TREC-‐Chem 2011 • Ranked 4/4
• PatOlympics 2010 • Ranked 1/2
• PatOlympics 2011 • Ranked 2/2
Related patent search
• TREC-‐Chem 2011 • Ranked 1/2
12 © University Hospitals of Geneva Division of Medical Information Sciences
Results: User interface
User-‐friendliness:
• PatOlympics 2010 • Ranked 1/5
• PatOlympics 2011 • Ranked 1/5
hfp://casimir.hesge.ch/TWINC
13 © University Hospitals of Geneva Division of Medical Information Sciences
Plan
1. IntroducKon
2. Methods
3. Results
4. Demo
5. Conclusion
14 © University Hospitals of Geneva Division of Medical Information Sciences
Demo
15 © University Hospitals of Geneva Division of Medical Information Sciences
Plan
1. IntroducKon
2. Methods
3. Results
4. Demo
5. Conclusion
16 © University Hospitals of Geneva Division of Medical Information Sciences
Conclusion
Ad hoc search & Related patent search • CompeKKve results for related patent search • Less encouraging results for ad hoc search
Chemical Query Expansion • FuncKonality very important to cope with different ways to name medicinal substances
TWINC • Usability appreciated by intellectual property specialists
17 © University Hospitals of Geneva Division of Medical Information Sciences
Thank you for your attention