PGCP - Plataforma para Gerenciamento Colaborativo de Projetos

Collaborative Systems are designed to support individuals in order to solve a problem together, or cooperatively (or collaboratively). Such systems have the advantage of not requiring the presence in the same location of the participants. The basis of any Collaborative System is communication, where users interact with each other in order to exchange information. Communication among individuals is accomplished through collaborative tools such as chat, email, document repository, etc.. Using these tools, companies can reduce operational costs, saving on travel and accommodation of its employees to attend meetings. The project members only need a computer with internet access to use collaborative tools. Project management is essential to the quality of the nal product. To perform a proper management, methodologies must be applied using methods, tools and procedures. There are some phases that are considered generic for all software process models, they are: de nition, development, maintenance and activity to support the software process. In this paper is described a platform for project management using the concepts and features of Collaborative Systems. The goal of this platform is to unify various collaborative tools (such as chat and document repository) in a project management system. Using the system, it becomes possible to manage projects, and the ability to maintain an active constant communication between members of each project

Selecting candidate labels for hierarchical document clusters using association rules

One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels have to be built using only the terms in the documents of the collection. This paper presents the SeCLAR (Selecting Candidate Labels using Association Rules) method, which explores the use of association rules for the selection of good candidates for labels of hierarchical document clusters. The candidates are processed by a classical method to generate the labels. The idea of the proposed method is to process each parent-child relationship of the nodes as an antecedent-consequent relationship of association rules. The experimental results show that the proposed method can improve the precision and recall of labels obtained by classical methods. © 2010 Springer-Verlag.

Improving hierarchical document cluster labels through candidate term selection

One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels must be built using all the terms in the documents of the collection. This paper presents the SeCLAR method, which explores the use of association rules in the selection of good candidates for labels of hierarchical document clusters. The purpose of this method is to select a subset of terms by exploring the relationship among the terms of each document. Thus, these candidates can be processed by a classical method to generate the labels. An experimental study demonstrates the potential of the proposed approach to improve the precision and recall of labels obtained by classical methods only considering the terms which are potentially more discriminative. © 2012 - IOS Press and the authors. All rights reserved.