Alneu de Andrade Lopes

• Abstract

  In the real world, textual format is the common way of storing information. Thus automated techniques which help 10 group, extract topic, and classify textual documents, minimizing the need of human intervention, remain a worthwhile research topic. In this context, the Brazilian and Canadian groups have developed a number of lechniques related to network-based text mining, to complement t…

  Graph-based total recall information retrieval on text document corpora, AP.R SPRINT

• Abstract

  Online social networks are web platforms that reflect the social networking structures of the real world, such as friendship, professional, family, and other networks. In recent years, the study of social networks has attracted the attention of the scientific community for its variety of applications such as: friendship, locations, and products recommendation systems, travel planning syst…

  Social Network Analysis and Mining, AP.R
• Brazilian Conference on Intelligent System (BRACIS 2012), AR.BR

• Abstract

  Fairness in Machine Learning is an area that aims to use techniques focused on mitigating discriminatory effects in decisions executed by Machine Learning, preserving as much as possible the accuracy of the decision. In this area, there are three possibilities of intervention to produce fairer classifiers, which are distinguished among them by the intervening stage. They are pre-processin…

  Pre-processing in minimizing discriminatory effects in classification tasks, BP.IC

• Abstract

  Complex networks is a novel research area in artificial intelligence to deal with real systems in which different parts interact. This systems can be social, biological, technological, or related to information represented as graphs with non-trivial topology and, in general, large-scale. Such graph, which we refer to as network, is represented by a set of vertices and a set of edges (or l…

  Prediction of links and vertices in scientific communities, BP.IC

• Abstract

  Location-based social networks (LBSN) are web platforms that reflect structures of social networks in the real world. In recent years, the study of LBSNs has attracted the attention of the scientific community, specially, because LBSNs consider information from user interactions and geographic location information for a period time, to develop applications such as location recommender sys…

  Mining User Behavior in Location-Based Social Networks, BP.DR

(Only some records are available in English at this moment)

• Abstract

  We intend to evaluate the syntactic plausibility of Syntactic Topic Model (STM). The STMis a non-parametric Bayesian model of parsed documents. The STM generates words thatare both thematically and syntactically constrained, which combines the semantic insightsof topic models with the syntactic information available from parse tress. The expertise thatwe wish to obtain from STM study incl…

  Evaluating syntactic topic models, BE.EP.DR