design principles for competence-based recommender systems

Collaborative Project – FP7- ICT- 2009 - 257886

Design Principles for Competence-

based Recommender Systems

Valerio Bellandi, Paolo Ceravolo, Fulvio Frati, Jonatan Maggesi Università degli Studi di Milano, Italy

Gabriela Waldhart, Isabella Seeber

Leopold-Franzens University of Innsbruck, Austria

IEEE DEST-CEE 2012 18-20 June 2012

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Outline

ARISTOTELE Project

Introduction on Recommender Systems

Recommendations in Competence Management Systems

Analysis of ARISTOTELE Recommender System Scenario

Competence-based Management System

Conclusions


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Modern knowledge-intensive organizations are step by step realizing that shifting the relevance from tangible to intangible assets increase competitiveness It is important to consider complex environments that integrate models,

processes and technologies with organizational aspects in a systemic approach

The FP7 ARISTOTELE research project aims at relating learning to organizational processes, as well as to the innovation process management

Three kinds of processes are identified: organizational processes (marketing & communication, HRM, business)

learning processes (group training sessions)

social collaboration processes (spontaneous formation of groups)

ARISTOTELE Project


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Recommender Systems (RSs) are considered critical in ARISTOTELE approach to exploit interactions in collaborative environments and foster the innovation process

Basic RS concepts: 1. Homophily: similarity between sources and recipients

2. Tie strength: intensity of the relationship between the recipient and source

3. Trust: trust relationship between recipient and source

4. Social capital: source’s reputation

Four main RS categories: 1. Content-based: RS calculates similarity of related contents

2. Collaborative: RS calculates similarity of user profiles basing on ratings

3. Knowledge-based: RS considers user requirements and domain knowledge

4. Hybrid

ARISTOTELE RS falls in the 4th category, taking care of all RS concepts

Recommender Systems - 1


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ARISTOTELE RS try to mix two important aspects of

modern RSs

Diversity, Novelty and Serendipity

Give to users suggestions that are not limited to the closest ones,

but also those suggestions that apparently are far from the user’s

interest, but she should also like it

“Serendipity is the art of making an unsought finding”

F.P. Adams

Knowledge-sharing and Solidity

The accuracy of recommendations will be improved with a

knowledge assessment service, exploiting users’ implicit and explicit

feedbacks on suggestions

Recommender Systems (RSs) - 2


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ARISTOTELE RS will assist the platform Competence Management System (CompMS)

Typical CompMS process: Identify the task to be completed

Perform a gap analysis to identify available and missing competences

Use the results to identify the actions to fill the learning gaps

Integration between RS and CompMS is difficult Example: suggestions on how a user can improve his CV cannot be

directly referred to users having similar CVs

It requires the definition of specific design principles for the algorithms guiding the recommendation process

Recommendations in CompMS


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The analysis started from the introduced RS concepts and ARISTOTELE platform user requirements

Four different analysis dimensions, taken from project user scenarios: Competence Based Management

Activity and Task Management

Collaboration

Knowledge

Result of the analysis will be in terms of preconditions and limitations, to define the boundaries of the ARISTOTELE RS Preconditions and limitations have been exploited for the design of

RS

Competence-based RS Principles


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ARISTOTELE will allow the representation and reasoning on related concepts

stored in the models

Contextual information, e.g. a person with specific competences working on a specific

task, can be reused to express relations

Precondition 1 - Competence Profiles

Competence profiles, and the awareness on which competences are required for

organizational tasks, are required

Competence profiles need to be accessible and updatable by the platform

RS must know to what extent a person is capable of fulfilling the task (proficiency)

The knowledge base must be designed around the basic concept of competence

Limitation:

In case competence profiles levels are not available, the RS will not be able to

suggest people related information

Competence Based Management - 1


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Precondition 2 - Tagging/Annotating

The platform needs to provide tagging or annotation

functionalities for artifacts, people, and processes

Users need to have the corresponding rights and willingness to

annotate available contents

Content-based recommendations are efficient only with the

availability of suitable tags or keywords

Limitation:

If users cannot tag or annotate contents or resources, it is likely

that recommender results will not reach high accuracy

Competence Based Management - 2


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ARISTOTELE supplies a comprehensive workflow

management, where people can define, refine, monitor,

and assign objects

Workers’ daily tasks can be improved with the help of accurate

resource recommendations

The RS should support community work by

recommending appropriate groups that hold necessary

expertise or resources

The platform needs to be able to merge information coming from

various sources, e.g. social networks, ERPs, CRMs

Activity and Task Management - 1


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Precondition 3 - Activity/Task Monitoring

RS needs to interface with the platform to extract necessary

information about users’ tasks/activities from enterprise systems

These systems need to provide endpoints to extract necessary

information about users’ tasks/activities

Users need to enrich tasks description with set of metadata that

will help RS to provide reliable suggestions

Limitation

If activity/task information are not available for recommendation,

ARISTOTELE methodologies related to it might be restricted

Activity and Task Management - 2


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User scenarios included possible communication channels: instant

messaging, private message, discussion boards, shared

workspaces, forums, meetings arrangement, workflow management

systems, …

Collaboration should result in annotations of users’ contents by

resource rating, tagging, or giving feedback or comments on

documents

Precondition 4) Willingness to change communication practices

It is necessary that the organizational culture, and therefore people, accept and

are willing to use ARISTOTELE communication channels

It is important that the RS will be able to access collaborative resources and

contents and give suggestions based on them

Collaboration


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ARISTOTELE core is the handling of explicit/codified

knowledge, giving the appropriate support of people to

exchange implicit knowledge successfully

The platform needs to support activities to update and

share organizational knowledge

Knowledge might also be found or stored outside the

organizational boundaries

It is important to find mechanisms to determine trustable and

justifiable knowledge sources

The platform needs to reach a critical mass of users and

contents to give reliable suggestions

Knowledge - 1


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Precondition 5) Migration of existing knowledge base

There is a need that the existing knowledge base gets migrated

into ARISTOTELE

Ontology matching techniques could achieve that same things from

diverse systems will be described as one thing

RS must rely on a common metamodel to be able to derive

suggestions from different sources

Limitation

If a knowledge base is not available, the platform could have

problems in solving the start-up problem and create sufficient

positive network effects

Knowledge - 2


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Precondition 6) Context Information

To derive contextual information ARISTOTELE needs to have

interfaces to other enterprise systems (CRM, HRM, ERP,…)

Information needs to be mapped among the different sources if

they deliver the same semantic information (e.g., worker, client,

user, etc.)

It is important to have a common metamodel to uniform all the

data

Limitation

If ARISTOTELE cannot draw on information stored elsewhere in

the organization, content-based recommendation will be highly

limited

Knowledge - 3


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Stated preconditions and limitations were inputs for the development of the ARISTOTELE RS

It differs from other common RS by taking as central concept the competences and working experiences of all members of an organizations

Designed to be triggered by a specific stimulus Giving suggestions on activities and learning plans correlated to the

subject

Suggesting a set of alternative objects that, at a first sight, could seem completely unrelated (serendipity)

RS can introduce novel and unexpected knowledge fields in the ordinary business process

ARISTOTELE Competence-based RS - 1


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ARISTOTELE Competence-based RS - 2


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We investigated important preconditions and limitations that are considered to have impacts on the design and success of a competence-based Recommender System

Preconditions can be directly used as input factors for the RS

Preconditions can inform the design of RS from a theoretical point of view with the goal to improve the acceptance of recommender results

Currently we are working on: The implementation of the RS within the ARISTOTELE platform

Validation of the approach through independent experiments Results of the validation presented during the Innovation Adoption

Forum

Conclusions

[email protected]

Thank you

Any questions?

ADDITIONAL SLIDES


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RS Metamodel – CR2S

design principles for competence-based recommender systems

Technology