Text Mining. A new approach in FFG to achieve deeper insights into project data. TAFTIE Expert Session Sept 14, 2017

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1 Text Mining A new approach in FFG to achieve deeper insights into project data TAFTIE Expert Session Sept 14, 2017 Harald Hochreiter, Daniel Vilsecker

2 INNOVATION MAPPING IN FFG FFG tried to map innovation trends from the projects we fund Thematic teams were created who met every 1-2 months to discuss projects and exchange experience (eg. mobility, services) Worked well for short term requests and strengthened thematic bridges between programmes and departments Did not succeed in identifying larger trends or develop thematic briefings that stakeholders would have been interested in Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 1

3 SENTIMENT ANALYSIS Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 2

4 MACHINE LEARNING Deepmind s AlphaGo computer program has recentely beat the human world champions of Go Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 3

5 TEXT MINING Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 4

6 Text Mining

7 DEFINITION OF TEXT MINING The overarching goal is to turn text into data for analysis, via application of natural language processing (NLP) and analytical methods. Text analysis involves information retrieval, lexical analysis to study word frequency distributions, pattern recognition, tagging/annotation, information extraction, data mining techniques including link and association analysis, visualization, and predictive analytics. (Source: Wikipedia) Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 6

8 WORD CLOUD OF MPG ACTIVITY REPORT Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 7

9 K-Means Clustering Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 8

10 FFG DATA project applications abstracts selected (german only, excluded specific programmes) Analysed with unsupervised k-means clustering aiming at 15 clusters Clusters containing between 238 and 2486 projects Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 9

11 Clustering vs SIC codes (Standard Industrial Classification codes)

12 K-Means Clustering (k=15) Clusters contain between 238 and 2486 projects Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 11

13 INDIVIDUAL CLUSTER 1344 kund softwar mobil plattform servic produkt automat digital app technisch prototyp onlin markt Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 12

14 INDIVIDUAL CLUSTER 450 patient klinisch medizin studi behandl erkrank human zell wirksam antikorp wirkstoff substanz therapeut Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 13

15 Clustering result vs SIC Codes Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 14

16 Identify trends over time

17 1.279 PROJECTS IN 2012 building / smart grid / energy led / durability / battery woman / needs facility / heat pump / electicity engine / gas vehicle / hybrid score / education pupil / teaching child / youth material / steel /ceramic raw material / biomass component / wood / plastic production / construction packaging / resilent processing / building substrate / bacteria surface / purification vaccine / disease medicine / patient laser / visual software / application / platform web / system / mobil sensor / calculate media / social Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 16

18 1.382 PROJECTS IN 2013 smart grid / energy IEA / tool solar / concept hybrid / adaptive vehicle / driving traffic / facility / multimodal photovoltaic child / youth women / men / social surface / lamination / diagnostic cell / protein patient / clinical raw material / chemical mobil / software emission / fuel / biomass material / steel / consolidation component / manufacturing alloy / copper waste / processing sensor / engine / automatic / control service / platform / onilne visualization / real-time optical / led big data / country Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 17

19 Self Organising Maps (SOM)

20 SOM Example (Scatter View) Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 22

21 SOM Example (Density View) Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 23

22 Next steps

23 NEXT STEPS Work on visualisation ( heatmaps et al) Start working on supervised learning using ontologies (e.g.: which projects contain aspects of digitisation? ) Analyse individual sectors (e.g.: what are the research trends in the forest industry? ) Scale up and integrate it into routine data analysis Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 25

24 FEEDBACK AND DISCUSSION Comments? Questions? Suggestions? Thank you! Österreichische Forschungsförderungsgesellschaft Sensengasse Wien 26