Labeling methods for association rule clustering

Although association mining has been highlighted in the last years, the huge number of rules that are generated hamper its use. To overcome this problem, many post-processing approaches were suggested, such as clustering, which organizes the rules in groups that contain, somehow, similar knowledge. Nevertheless, clustering can aid the user only if good descriptors be associated with each group. This is a relevant issue, since the labels will provide to the user a view of the topics to be explored, helping to guide its search. This is interesting, for example, when the user doesn't have, a priori, an idea where to start. Thus, the analysis of different labeling methods for association rule clustering is important. Considering the exposed arguments, this paper analyzes some labeling methods through two measures that are proposed. One of them, Precision, measures how much the methods can find labels that represent as accurately as possible the rules contained in its group and Repetition Frequency determines how the labels are distributed along the clusters. As a result, it was possible to identify the methods and the domain organizations with the best performances that can be applied in clusters of association rules.

Metrics to support the evaluation of association rule clustering

Many topics related to association mining have received attention in the research community, especially the ones focused on the discovery of interesting knowledge. A promising approach, related to this topic, is the application of clustering in the pre-processing step to aid the user to find the relevant associative patterns of the domain. In this paper, we propose nine metrics to support the evaluation of this kind of approach. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Some experiments were done in order to present how the metrics can be used and their usefulness. © 2013 Springer-Verlag GmbH.

QCD sum rule study for a possible charmed pentaquark Θ c(3250)

We use QCD sum rules to study the possible existence of a Θc(3250) charmed pentaquark. We consider the contributions of condensates up to dimension 12 and work at leading order in αs. We obtain mΘc=(3.29±0.13) GeV, compatible with the mass of the structure seen by BABAR Collaboration in the decay channel B-→p̄Σc++π-π-. The proposed state is compatible with a previous proposed pentaquark state in the anticharmed sector. © 2013 American Physical Society.

Allometry for Sexual Size Dimorphism in Stoneflies Defies the Rensch's Rule

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fuzzy rule-based system for evaluation of uncertainty transaction in cassava chain

A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

Metrics for Association Rule Clustering Assessment

Issues related to association mining have received attention, especially the ones aiming to discover and facilitate the search for interesting patterns. A promising approach, in this context, is the application of clustering in the pre-processing step. In this paper, eleven metrics are proposed to provide an assessment procedure in order to support the evaluation of this kind of approach. To propose the metrics, a subjective evaluation was done. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Besides, the metrics do the users think about aspects related to the problems and provide a flexible way to solve them. Some experiments were done in order to present how the metrics can be used and their usefulness.

Heavy λ semileptonic decay: A QCD sum rule approach

In this work we calculate the form factors of the Lambda(c) and Lambda(b) semileptonic decay using the QCD sum rules approach. We found that the form factors sum rules are more stable than the respective mass sum rules, and we get a decay rate for Lambda(c) compatible with experiment.

QCD sum rule approach to the s->d gamma contribution to the Omega(-)->Xi(-)gamma radiative decay

QCD sum rules are used to calculate the contribution of the short-distance single-quark transition s-->d gamma to the amplitudes of the hyperon radiative decay Omega(-)-->Xi(-) gamma. We reevaluate the Wilson coefficient of the effective operator responsible for this transition. We obtain a branching ratio which is comparable to the unitarity limit.