#CeDEM13 Day 2 afternoon, Reflections, Main Hall, Chair: Morten Meyerhoff Nielsen

1. Refining public sector services by
applying innovative technologies
Bojan Cestnik 1, 2
Alenka Kern 3
1 Temida d.o.o., Ljubljana, Slovenia
2 Jožef Stefan Institute, Ljubljana, Slovenia
3 The Housing Fund of the Republic of Slovenia, Ljubljana, Slovenia

2. Talk outline
— Motivation and introduction
— Case studies
◦ CeDEM 2011 papers topic ontology
◦ Temporal focus shift of topics
◦ Outlier documents detection – search for innovative leap of
ideas
— Conclusions and further work

3. Motivation I
— Hypothesis: tools like
– text exploration,
– document clustering, and
– literature mining
◦ have a potential to support the process of innovative problem
solving
– in e-government domain
◦ by bridging information from different disciplines
— Source: E-Government Reference Library (EGRL)
◦ 4.674 peer-reviewed articles published in the last decade

4. Motivation II
— Creativity is a universal virtue
— Two kinds of creativity (G.A.Wiggins, 2012)
◦ Spontaneous creativity (ideas appear spontaneous in
consciousness)
– e.g. Mozart: „When I am, as it were, completely myself, entirely
alone, and of good cheer – say traveling in a carriage, or walking after
a good meal, or during the night when I cannot sleep; it is on such
occasions that my ideas flow best and most abundantly.“ (Holmes,
2009, p. 315)
◦ Creative reasoning
– The composer working to build a new version of a TV theme, on
schedule and with constraints on „acceptable style“
— The computer software is the tool, the user is the creator
— Computational Creativity as an emerging field

5. Motivation III
— Increasing number of documents within all areas of human
expertize
— Difficult to follow the progress even in a single specific area
— Innovative behavior is related to the comprehension of a particular
field

6. Literature mining
— Technologies:
◦ Associative retrieval based on simple keywords
◦ Inductive pattern search
◦ Novelty: cross-context search incorporating scientific theories
and models
— Knowledge discovery process involves:
◦ Mining dynamic data streams
◦ Incrementally updating existing models and theories
— Observation: vast majority of the mappings between scientific
models and theories has been carried out exclusively by the human
scientists

7. Case studies
— First study: CeDEM 2011 topic ontology
— Source: E-Government library (Scholl, 2012)
— Second study: explore temporal focus shift, compare focus shifts of
titles and abstracts
— Third study: outlier documents detection – rare and worthwhile
for additional exploration since they might contribute to creative
leap of ideas

8. CeDEM 2011 papers

9. E-Government library (Scholl, 2012)
Titles Abstracts
Publication year Number % Number %
2002 and before 515 11,0 281 10,3
2003-2004 706 15,1 479 17,5
2005-2006 813 17,4 331 12,1
2007-2008 938 20,1 500 18,3
2009 679 14,5 427 15,6
2010 637 13,6 420 15,3
2011 386 8,3 301 11,0
Total 4.674 100,0 2.739 100,0

10. Focus shift through time – titles

11. Motivation IV
— Help experts in cross-domain discovery of new previously unknown
relations by supporting bisociative discovery
— Bisociation:
◦ Term coined by Arthur Koestler,The act of creation, 1964
◦ Bisociation is "any mental occurrence simultaneously associated
with two habitually incomparable contexts“ - Koestler considered
it the essential mechanism of the creative process
◦ The goal of FP7 EU Project BISON (Bisociation Networks for
Creative Information Discovery): explore the concept of
bisociative discovery using graph-based data mining
— When we all think alike, no one thinks very much (A. Einstein)

12. Outlier documents detection
innovative,
technology, service,
adopted, creativity,
local, citizens,
applications, diffusion,
challenges
management, studies,
discuss, relationship,
effectiveness,
presented, proposes,
security, offer,
framework
E-Goverment library
documents
similarity

13. Document clustering
— Outliers: good candidates to search for relations between concepts

14. An example of bisociation
Dr. Lawrence J. Fogel

15. Conclusions
— Presented case studies explore technological possibilities for
supporting creative processes in public sector
— Ontologies can be used for studying temporal focus shift within a
given domain
— Experts can use document clustering and similarity measures to
support cross-domain discovery of new previously unknown
relations (bisociative discovery)