The Computer Journal Advance Access originally published online on February 12, 2009
The Computer Journal 2009 52(7):789-798; doi:10.1093/comjnl/bxp002
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This article appears in the following The Computer Journal issue: Incorporating Profiling Expertise and Behaviour Special Issue [View the issue table of contents]
i-ProSE: Inferring User Profiles in a Scientific Context
1 PURO/UFF, Science and Technology Department, Fluminense Federal University, Rua Recife, s/n, Jardim Bela Vista - Rio das Ostras, RJ, Brazil CEP 28890-000
2 Institute of Mathematics and Statistics, UERJ/IME, State of Rio de Janeiro University, Rua são Francisco Xavier, 524 - Pavilhão Reitor João Lyra Filho6° andar - Sala 6019 - Bloco B - Rio de Janeiro, RJ, Brazil CEP 20559-900
3 Graduate School of Computer Science, COPPE/UFRJ, Cidade Universitária, Centro de Tecnologia, Bloco H, Sala 319 Caixa Postal: 68511 Rio de Janeiro, RJ, Brazil CEP 21941-972
4 DCC/IM, Institute of Mathematics, Federal University of Rio de Janeiro
* Corresponding author: avivacqua{at}addlabs.uff.br
Received 13 November 2008; revised 13 November 2008
Scientific environments are known for being highly dynamic, subject to rapid evolution and demanding constant renewal and update. Additionally, science is a highly social arena. However, interpersonal collaboration and knowledge flow in scientific environments are usually more restricted. Collaboration is intense among small groups of people working on specific problems within a domain, but low between groups. As user profiling has been extensively used as a basis for recommendation, personalization and matchmaking systems, a better profile identification can improve interaction levels among researchers belonging to the same domain but working in different laboratories. Profiles may be constructed in two ways: either through explicit declaration by the user or through the observation of users’ actions. Many systems employ one approach to the exclusion of the other. We contend that a combined approach will yield better results, especially on scientific scenario, providing a mix of declared and inferred information. In this article, we present inference-based profiles in scientific environments (i-ProSE), an integrated system that dynamically creates and maintains scientific user profiles based both on declared information and on observed behaviour. The i-ProSE can be used to locate experts, deliver content, build communities, find collaborators for long-term projects or detect instantaneous opportunities for informal collaboration, which is presented with a short study case.
Key Words: user profile • scientific profiles • matchmaking