ARISTOTELE approach has been presented at the Innovation Adoption Forum for Industry and Public Sector within the 6th IEEE International Conference on Digital Ecosystem Technologies (IEEE DEST - CEE 2012). The presentation about ARISTOTELE has been held by Paolo Ceravolo and Ernesto Damiani (University of Milan) during the keynote "The Innovation Engine for Team Building – The EU Aristotele Approach". Learn more on http://www.aristotele-ip.eu/

1. The Innovation Engine for Team Building –
The EU Aristotele Approach
From Open Innovation to the Innovation Factory
Ernesto Damiani – Paolo Ceravolo
Università degli Studi di Milano

2.  Innovation
 Open Innovation
 The ARISTOTELE Innovation Factory
 Recommendation in Collaborative Environments
 Lesson Learned
 Future Works
Outline

3.  Innovation is the catalyst to economic growth.
 Joseph Schumpeter famously asserted that “creative destruction is
the essential fact about capitalism.” Entrepreneurs continuously
look for better ways to satisfy their consumer base with improved
quality, durability, service, and price which come to fruition in
innovation with advanced technologies and organizational
strategies.
 There are several sources of innovation. According to the Peter F.
Drucker the general sources of innovations are different changes
in industry structure, in market structure, in local and global
demographics, in human perception, mood and meaning, in the
amount of already available scientific knowledge, etc.
Innovation

4.  Open Innovation is the use of purposive inflows and outflows of
knowledge to accelerate internal innovation and expand the
markets (Chesbrough 2003).
 Innovation is seen as an outcome of a collision between
technological opportunities and user needs. The focus is upon the
interaction between producers and users.
 One outcome of this approach is a more realistic understanding of
markets and vertical integration than the ones offered by
neoclassical economics and transaction economics.
 Another outcome is treating research and development as
collaborative and open systems.
Open Innovation

5.  ARISTOTELE research project is an IP funded under
the EC FP7.
 The aim is relating the learning process to the
organizational one (including innovation process
management). In particular:
 Organizational processes (marketing&communication, human
resources management, business)
 Learning processes (group training sessions)
 Social collaboration processes (spontaneous formation of
groups within the organization)
ARISTOTELE Project

6.  Supports addressing ill-defined, vague needs and
transforming them into requirements or virtual products
 Suggestions are derived based on open-innovation-
sources like help desk messages
 Reactive mode only (for now)
Innovation Factory

7. Innovation Factory

8. Innovation Factory

9. Innovation Factory

10.  Methodology can draw upon three different types of
resources
 Results of a Collaborative Innovation Framework that describes
needs and general requirements for new products/services
 External Stimuli, posing challenges related to innovation and
competence improvement, ordinarily, not specified in terms of
resources
 Explicit enterprise knowledge formalized in instances of the
ARISTOTELE models, mainly in the Knowledge, Competence
and Worker models
Methodologies to Foster the Innovation
Factories (1)

11.  The information sources of innovation process are of
three types:
 Contributions coming from innovation workers, defining or
brainstorming requirements for a new product
 Contributions coming from partners (i.e. employees, suppliers,
customers) who send comments and ideas that can be
collected and transformed in requirements to be analyzed
 Contribution from external sources, e.g. using a software
crawler to analyze electronic resources and extract information
(e.g. web site competitors, forums, blogs)
Methodologies to Foster the Innovation
Factories (2)

12.  The results of the methodology can be represented by:
 Suggestions sets regarding new products or services
 Proposals of innovative activities and their impact on the
organization
 Suggested interactions with experts and peers that may
improve creativity in the organization
Methodologies to Foster the Innovation
Factories (3)

13.  The outputs of the first stage of Innovation Factory
(Virtual Product Designer) can be used to generate VPs
Workflow (1)
Virtual Product
Designer
Recommender
System
Innovation
Support SystemVirtual
Product
Suggestions
Target: Working
Team
Configuration
Settings
Explicit Organization
Knowledge
External Stimuli

14.  The VP definition, annotated with requirements and
requested competencies, is used as stimulus for the
Recommender System
Workflow (2)
Virtual Product
Designer
Recommender
System
Innovation
Support SystemVirtual
Product
Suggestions
Target: Working
Team
Configuration
Settings
Explicit Organization
Knowledge
External Stimuli

15.  Last stage of the workflow (Innovation Support System)
gives suggestions to personal learning plans specific
for workers profiles and organization needs
Workflow (3)
Virtual Product
Designer
Recommender
System
Innovation
Support SystemVirtual
Product
Suggestions
Target: Working
Team
Configuration
Settings
Explicit Organization
Knowledge
External Stimuli

16.  Stimulus: “A lot of complaints reach our help-desk”
 Crawler selects some components, most turn out to be
about lazy tech assistance
 Brainstorming in VP points at shorter response time,
but highlight high marginal cost of achieving it
Example (1)

17.  SM: guidelines on tech assistance
 DM: entries from champion’s blog praising good
assistance
 Entries about latest read of champion,
the book “Neuromancer”, is about
small communities taking over
Example (2)
SERENDIPITY!!

18.  Seve teams. Each team was assigned with a task to be
accomplish in a limited timespan
 The members of the team was placed in different
rooms and was provided with IF (mikiwiki based)
 The IF was the only tool allowed for cooperating and
communicating in the team, all other channels to
access the web was disabled
 Four teams was set as experimental groups and was
provided with the ARISTOTELE RS
 Three teams was set as control groups and was
provided with the standard IF services
Experiment

19.  H1: experimental groups will develop a communication
process more linear, with less objections and rejects on
the arguments proposed during the discussion
 H2: experimental groups will develop the task in a more
linear process, executing activities in a more ordered
flow
 H3: experimental groups will develop the task with
better result in time management, distributing the
activities on the whole timespan
Experiment

20. Results: global activities performed
EX
Teams
EX
Teams

21. Results: global activities performed
CON
Teams
CON
Teams

22. Results: spec. activities performed
EX
Teams
EX
Teams

23. Results: spec. activities performed
CON
Teams
CON
Teams

24. Results: conversation actions
EX
Teams
EX
Teams

25. Results: conversation actions
CON
Teams
CON
Teams

26. Results: conversation flow
EX TeamsEX Teams

27. Results: conversation flow
CON TeamsCON Teams

28.  Hypothesis are confirmed
 H1: experimental groups will develop a communication process
more linear, with less objections and rejects on the arguments
proposed during the discussion
 H2: experimental groups will develop the task in a more linear
process, exe- cuting activities in a more ordered follow
 H3: experimental groups will develop the task with better result
in time management, distributing the activities on the whole
timespan
 What does it means?
Experimental Results

29.  RSs have reached in the last years a good level of ac-
curacy
 Our experiment show that RSs can have good impact
on reducing the overhead required to a tem for
collaborating
 RSs however can create a close community
 RSs still fail in discovering users latent interests: they
often suggest items that, although accurately tailored
on the users’ past behavior, and create communities
that are overspecified
Overspecialisation Problem

30.  Modern RSs contaminate users experience with
dissimilarity: dissimilarity can increase users’
satisfaction and stimulate latent interests
 Mentor Approach: instead of choosing a random
musical world, to exploit the knowledge of the best
reputed users
 Instead of taking into consideration the set of all the
items to select suggestions, we prefer items exploited
by mentors
 this means that this approach could for example prefer, as
neighbour for a user Ui, user Uj respect to user Uz even if
similarity(Ui, Uj) < similarity(Ui, Uz) if Uj is an eclectic user and
Uj is not
The mentor approach

31. Thank you
Any questions?

32. ADDITIONAL SLIDES

33.  V. Bellandi, P. Ceravolo, E. Damiani, and F. Frati. CR2S: Competency Roadmap to Strategy. Proc.
of 1st Int. Workshop on Knowledge Management and e-Human Resources Practices for Innovation
(eHR-KM ‘11), 2011
 R. Phaal, C.J.P. Farrukh, D.R. Probert. Technology roadmapping - A planning framework for
evolution and revolution. In Technological Forecasting and Social Change 71:1, January 2004
 F. Ricci, L. Rokach, B. Shapira, P.B. Kantor (Eds.). Recommender Systems Handbook, Springer,
2011
 R. Maier. Knowledge Management Systems: Information and Communication Technologies for
Knowledge Management. Knowledge Management. Springer, 2007
 L. Iaquinta, M. de Gemmis, P. Lops, G. Semeraro. Recommendations toward Serendipitous
Diversions. In Proc. of Ninth International Conference on Intelligent Systems Design and
Applications, 2009
 P. Ceravolo, E. Damiani, M. Viviani. Bottom-up Extraction and Trust-based Refinement of
Ontology Metadata. IEEE Transactions on Knowledge and Data Engineering 19 (2), 2007
 G. Adomavicius, A. Tuzhilin. Toward the next generation of recommender systems: a survey of the
state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering,
17(6), 2005
 P.S. Adler, C. Heckscher. Towards Collaborative Community. In The Firm as a Collaborative
Community: Reconstructing Trust in the Knowledge Economy. Oxford University Press, 2006
 A. Hargadon, R.I. Sutton. Innovation Factory. Harvard Business Review, 2000
 C. Edquist. Systems Of Innovation: Perspectives and Challenges. In J. Fagerberg, D. C. Mowery,
& R. R. Nelson (Eds.), The Oxford Handbook of Innovation. New York., 2005
References