Lucas R. B. Schmitz’s scientific contributions

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Publications (4)


1370-3863-1-PB versao publicada
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July 2013

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58 Reads

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Eduardo Ribas Pinto

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Figure 1. S WEETS architecture. 
Figure 2. Co sine Formula (Baeza-Yates and Ribeiro, 1999).
Figure 3. Behavior of users when solving a problem. 
Figure 4. Lightweight ontology O emerged in a.m.i.g.o.s. ci 
Figure 5. Interface of SWEETS 2.0 in a.m.i.g.o.s. 

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Recommending knowledge in a knowledge based social network

July 2011

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58 Reads

Journal of Applied Computing Research

The organizations aim to increase its competitiveness. In this context, they have been searching for new ways to improve their productivity, the quality of their products, and cost reduction. To achieve these goals, it is essential to use the collaborators’ potentials and the relationship among them to find and share tacit knowledge. Since tacit knowledge is stored in people’s mind, it is hard to be formalized and documented. Facing this difficulty, identifying and recommending persons who retain the needed knowledge might be a good option. This work presents the Specialist Recommender System (SWEETS) and its application into the a.m.i.g.o.s. environment, a social network platform for knowledge management. The SWEETS system uses folksonomy to extract a lightweight ontology, which is essential to effectively identify people’s skills. This lightweight ontology is based by tags (concepts) relating them to items (instances), and its co-occurrences. In addition, such ontology is domain independent, which is a contribution of this work. Applying the SWEETS system into the a.m.i.g.o.s. environment we are looking for minimizing the communication problem in the corporation, providing an improvement on knowledge sharing. Therefore, a better usage of the collaborators knowledge may be expected. Key words: SWEETS, social network, knowledge management



Recommending Domain Experts in a Social Network

October 2009

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139 Reads

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3 Citations

This paper presents the expert recommender system, called SWEETS, in its version 2.0, and its implementation in the environment A.M.I.G.O.S., a web based social network (WBSN). This environment is used as a communication and cooperation tool among employees from C.E.S.A.R. – a Brazilian innovative institute in software products. SWEETS uses folksonomy’s emergent ontology to spread the employees’ tacit knowledge throughout the company and thus an interaction improvement will be developed among them. By this, the communication and cooperation among the C.E.S.A.R. employees tend to significant improvements.

Citations (1)


... Estes relacionamentos podem ser uni ou bidirecionais, por exemplo: a) unilateral: enquanto A explicita que é colega de trabalho de B, o segundo não confirma este relacionamento; e b) bilateral: se uma pessoa A é colega de trabalho de B, então, como consequência, B também será colega de trabalho de A. As redes sociais proporcionam um ambiente informal e livre, em que as pessoas colaboram, de forma ad hoc, através de interações sem nenhum planejamento – o que, segundo [3], é um facilitador na troca de experiência entre as pessoas. Este é um dos argumentos que pode justificar os interesses das organizações em prover ambientes desta natureza como alternativa para a gestão interna de conhecimento, conforme os trabalhos desenvolvidos por [4], [5], [6] e [7]. Nestas organizações, prover uma ferramenta que possa atuar como incentivador à colaboração, é essencial para aumentar as potencialidades de exploração do capital intelectual. ...

Reference:

T-SWEETS: An Alternative to the Stimulus Collaboration from Trust Inference in Social Networks
Recommending Domain Experts in a Social Network