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.

Hallazgos de neuroimagen y desempeño ortográfi co de estudiantes con trastorno por défi cit de atención con hiperactividad según la semiología de los errores

Aim: To characterize, compare and classify the performance of students with attention deficit-hyperactivity disorder (ADHD) according to the semiology of errors and to describe the neuroimaging findings in these students. Methods: We evaluated 36 primary school boys and girls aged between 8 and 11 years old in the 3 rd to 5 th grades. The children were divided in two groups. Group I consisted of 18 students with an interdisciplinary diagnosis of ADHD (60% boys and 40% girls). Group II consisted of 18 children with good academic performance, paired by gender, age and grade with children in group I. The collective and individual versions of the Pro-ortografia spelling tests were applied. Results: Statistically significant differences were found in almost all the tests of the individual and collective versions of the spelling evaluation, with children with ADHD showing a higher average number of errors. Neuroimaging examinations indicated that 81% of the students in GI showed hypoperfusion in the frontal lobe, 7% had hypoperfusion of the thalamus and basal ganglia, 6% showed hypoperfusion in the basal ganglia only and 6% showed hypoperfusion in the left and right frontal lobes. Conclusions: Children with ADHD demonstrated poorer knowledge of the use of spelling rules in Brazilian Portuguese, which could be related to changes in blood flow in the frontal lobe, parietal lobe, thalamus and basal ganglia. These changes could cause a lack of attention, affecting phonological working memory and the planning of writing. © 2011 AELFA.

Fiscal rules and countercyclical policy: Frank Ramsey meets Gramm-Rudman-Hollings

Incluye Bibliografía

Fiscal rules for subnational governments in the EMU context

Includes bibliography

Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach

The multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.

Multi-relational algorithm for mining association rules in large databases

Multi-relational data mining enables pattern mining from multiple tables. The existing multi-relational mining association rules algorithms are not able to process large volumes of data, because the amount of memory required exceeds the amount available. The proposed algorithm MRRadix presents a framework that promotes the optimization of memory usage. It also uses the concept of partitioning to handle large volumes of data. The original contribution of this proposal is enable a superior performance when compared to other related algorithms and moreover successfully concludes the task of mining association rules in large databases, bypass the problem of available memory. One of the tests showed that the MR-Radix presents fourteen times less memory usage than the GFP-growth. © 2011 IEEE.

Post-processing association rules with clustering and objective measures

The post-processing of association rules is a difficult task, since a large number of patterns can be obtained. Many approaches have been developed to overcome this problem, as objective measures and clustering, which are respectively used to: (i) highlight the potentially interesting knowledge in domain; (ii) structure the domain, organizing the rules in groups that contain, somehow, similar knowledge. However, objective measures don't reduce nor organize the collection of rules, making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, making the search for relevant knowledge not so easy. This work proposes the PAR-COM (Post-processing Association Rules with Clustering and Objective Measures) methodology that, combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. Thereby, PAR-COM minimizes the user's effort during the post-processing process.

PAR-COM: A new methodology for post-processing association rules

The post-processing of association rules is a difficult task, since a huge number of rules that are generated are of no interest to the user. To overcome this problem many approaches have been developed, such as objective measures and clustering. However, objective measures don't reduce nor organize the collection of rules, therefore making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, therefore making the search for relevant knowledge not so easy. In this context this paper presents the PAR-COM methodology that, by combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. An experimental study demonstrates the potential of PAR-COM to minimize the user's effort during the post-processing process. © 2012 Springer-Verlag.

Rules of origin: new implications

Includes bibliography

What are fiscal rules for?: a critical analysis of the Argentine experience

Includes bibliography

Trade and investment rules: Latin American perspectives

Includes bibliography

Draft revised text of the constituent declaration and functions and rules of procedure of the Caribbean Development and Cooperation Committee as adopted by the 19th Session of the CDCC, 13-14 March 2002. Note by the Secretariat

Includes bibliography

Terms of reference and rules of procedure of the Economic Commission for Latin America and the Caribbean

Presenta las atribuciones y reglamentos de la Comisión en cuanto a las reuniones, la Secretaría, las votaciones, los idiomas, los informes, etc.