1. UpdataCapital The Context The Application Latest technical developments

2. The Human Touch Searching for documents or knowledge? –Knowledge is embedded in people –Collexis behaves like a (human) expert –Collexis finds information, experts and organizations –Collexis enhances Knowledge sharing and Collaboration

3. Human Communication Humans communicate in explicit language including many variations and ambiguities final aim of communication is sharing “concepts” Concepts are “real life entities” constituting the reference framework of human knowledge

4. Text search versus Concept search Word drivenSubject driven (concepts) Only exact wordsAlso synonyms and variants (normalization) No relative weight of wordsRelative weight of subjects (conceptual fingerprint) Low accuracyHigh accuracy Moderate performanceHigh performance Limited size of search textNo limitation in search text size

5. Basic Issues Coordination and facilitation of Information Sharing People/Experts Agencies/Departments/Organisations Document/Projects Interrelationship

6. Basic elements of Collexis’ Technology Collexis  Conceptual FingerPrinting Thesauri Data and metadata validation Flexible organisation/communication

7. The power of Fingerprints Collexis is based on the principle of Fingerprinting Fingerprint: a profile of a piece of information A Fingerprint contains a list of weighted concepts Concepts are derived from a Thesaurus Fingerprint characteristics: unique and small

8. Acronym Organisation contact details e-mail IOC text Categories (hidden but searchable) text Accpeted concepts Title /descriptors Name: Institute contact details e-mail IBC Organisations People Activities dynamic links output as dynamic combinations FTC Basic thinking: Basic Functionality

9. Fingerprints (CFP’s) C19881 0.99 C92992 0.67 C02002 0.66 C99229 0.44 C00392 0.33 C93939 0.21 consolidated knowledge C19881 0.99 C92992 0.67 C02002 0.66 C99229 0.44 C00392 0.33 C93939 0.21

10. 100% Malaria 35% Agencies 30% Enthusiastic 28% Collaboration 27% Funding 27% Africa 25% Science 15% Dedications 15% Applaud 15% agenda 14% Inaccurate 14% advocacy 13% hope 13% research funding 13% Fund Raising The Collexis  Fingerprinting concept

11. Defining a Search Word-based Searching What? Why? How? Who? indexing Concept matching

12. The magic of Fingerprinting contents fingerprints add people fingerprints add organization fingerprint Jobs CV’s, Skills Articles, books Emails, Word RFP’s

13. C19881 0.99 C92992 0.67 C02002 0.66 C99229 0.44 P00392 P00392 n.a O93939 O93939 n.a Semantic types Co-occurrence data The construction of Knowlets®

14. Name: A Institute contact details e-mail IBC text Acronym Organisation contact details e-mail DOI metadata text Title metadata DOI The “knowlet®” Connecting: content, people, organisations

15. content, people, organisations Publications Molecular Databases Image databases Patents Events Calls

16. Aircraft Airplane Simplified Thesaurus example Means of transport Train Automobile Car Truck Lorry Motor Vehicle Plane

17. Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text tt text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text etc. Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text t text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text etc. more text text Text text text Text text text Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text etc. more and more text text Text text text Text text text Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text etc. more text text Text text text Text text text Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text etc. text Text text text etc. more text text Text text text Text text text Text text text Text more text text Text text more text Text text text Text more and more text text Text text text Text text text etc. Search text or Document Removing Stop words Removing Stop words Normalization Concept Lookup Frequency Similarity Specificity Determination of relevant concepts Determination of concept weight Selected Concepts Selected Concepts Concept Search / Document Fingerprint Search / Document Fingerprint Source Result Clustering Abstraction Component

18. Name Address ID number Metadata Text Including unstructured metadata indexing Fingerprint Name Address ID number Metadata Data versus Metadata Attach metadata to Fingerprint

19. Collexis  characteristics Precision: only relevant documents are shown Recall: all relevant documents should be shown even when narrowing the search Performance: even in millions of documents, search results are provided instantly Human approach: not only documents, but also experts and organizations are the result of a search Structured & non-structured data: searching in both sources is possible in one action

20. The Collexis Solution Omnivore Collexis accepts structured and unstructured information Adaptable Collexis respects existing databases and does not require large hardware investments Accurate and sensitive Collexis Fingerprints are highly sensitive and accurate, and can be manipulated to optimize search results Fast in any language Collexis works across languages. Results are presented in milliseconds Immediate acceptance Collexis is easy to work with as it functions like a human mind

21. Nature Publishing Group about Collexis  “ While equivalents to some of the component parts of the technology exist, taken as a whole package it seems to me by far the most innovative software to date for research networking/many aspects of the research/electronic publishing enterprise. The system seems to go well beyond existing systems in terms of overall coherence, dynamic linking and Web interfacing”. Declan Butler Nature Publishing Group

22. Some Collexis clients: National Institute of Health World Health Organization Nature Publishing Group, London, UK Elsevier Science, New York, USA The Netherlands Organization for Scientific Research (NWO) Ministry of Science, The Netherlands Ministry of Education, The Netherlands Ministry of Economic Affairs, The Netherlands Compendium, The Netherlands World Bank, Washington, USA United Nations, Food & Agriculture Organization, Rome, Italy National Research Councils, like INSERM, GTZ, MRC, etc.

23. Executive PresentationKnowledge Management Collexis® Architecture Collexis® & Fingerprinting Overview RETURN