Collaborative Project – FP7- ICT- 2009 - 257886

METHODOLOGIES TO EXPLOIT COLLABORATIVE NETWORKS

UMIL, UIBK, CRMPA, PHI

2nd Review Meeting, Sep 2012 2

Methodologies to Exploit Collaborative Networks (1) One of the objectives of ARISTOTELE is orienting the construction of

knowledge according to the objectives and strategies of the organization

The methodology proposed in D6.4 focuses on the definition of a recommendation service aimed at: Inciting the collaboration selecting relevant knowledge generated in the

organization Increasing the frequency of interactions among users

D6.4 main contributions:

Extending the ARS with a closure path for balancing precision and recall Equipping the ARS with a hybridizer module that merges suggestions from

three search components Extending the ARS with a Feedback Analyzer

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Methodologies to Exploit Collaborative Networks (2)

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Takes three different input categories formalized as instances of ARISTOTELE models: Enterprise strategies and goals, driving process or task execution and providing a reference

to the business rational that justify the activities of the organization. Internal Stimuli, requesting the activation of collaborative actions External Stimuli, requesting to face market challenges by innovation and competence

improvement

An important input is the output of gap analysis produced in the Methodology for Decision Support on HRM (WP5)

Methodologies to Exploit Collaborative Networks (3)

Category Metamodel Nodes

Enterprise Strategies & Goals Strategy, Activity

Internal Stimuli Activity, Human Resource, Competency, Workproduct

External Stimuli Collaborative System, Electronic Resource, Interaction

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The outputs generated by our methodology are suggestions, again expressed in terms of ARISTOTELE models (via our metamodel) Documentation, resources and experiences to be added in the

PWLE Experiences and interactions that can improve creativity in the

organization Affinities that can simplify task execution and resource

exploitation

Increase the exploitation of enterprise social capital

Methodologies to Exploit Collaborative Networks (4)

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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 suggestions are accurately tailored on the users’ past behavior

and foster the creation of over-specified communities

Overspecialisation Problem

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Modern RSs contaminate users experience with dissimilarity Dissimilarity can increase users’ satisfaction and stimulate latent

interests

We applied the Mentor Approach: an approach successfully applied in the musical domain to exploiting 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

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Ranking and Justification Suggestions

The new technique we adopted has the advantage of providing a way for balancing expected precision and recall Suggestions are ranked according to their relevance based on

multiple criteria

For each suggestion, we can define our ranking function Rk as follows:

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Architecture

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An experiment is described to explore at what extent ARS can modify the flow of computer-supported collaborations

Our findings show that ARS has a positive impact on both the outcome and the structure of collaborations

Some anecdotal evidence collected during the experiment hits that ARS impacts on both the outcome and the structure of collaborations

Qualitative analysis of the collaboration flow suggests that ARS acts on the flow of collaboration, regulating how information is passed from participant to participant

Experiment

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References