Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts

The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.

Maternal Depression, Behavioral Profile and School Performance in School-Age Children

The aim of this study was to compare behavioral profile and school performance of school-age children living with a mother who presents clinical history of recurrent depression, diagnosed according to CID-10 criteria in order to verify the influences of such adversity. Thirty-eight mother-child dyads were evaluated using tests, interviews and questionnaires. Approximately two-thirds of the children presented behavioral and school performance difficulties with predominance of emotional and relationship problems, and impairment in the three areas of school performance which were assessed (writing, arithmetic and reading). Such difficulties may be associated with the negative impact of maternal depression. One-third of the children did not present difficulties, which suggests the use of protective mechanisms. The study highlights the importance of considering differences in children's profiles for the planning of mental health practices.

GRBAS and Cape-V Scales: High Reliability and Consensus When Applied at Different Times

Objectives. To evaluate whether the overall dysphonia grade, roughness, breathiness, asthenia, and strain (GRBAS) scale, and the Consensus Auditory Perceptual Evaluation-Voice (CAPE-V) scale show the same reliability and consensus when applied to the same vocal sample at different times. Study Design. Observational cross-sectional study. Methods. Sixty subjects had their voices recorded according to the tasks proposed in the CAPE-V scale. Vowels /a/ and /i/ were sustained between 3 and 5 seconds. Reproduction of six sentences and spontaneous speech from the request "Tell me about your voice" were analyzed. For the analysis of the GRBAS scale, the sustained vowel and reading tasks of the sentences was used. Auditory-perceptual voice analyses were conducted by three expert speech therapists with more than 5 years of experience and familiar with both the scales. Results. A strong correlation was observed in the intrajudge consensus analysis, both for the GRBAS scale as well as for CAPE-V, with intraclass coefficient values ranging from 0.923 to 0.985. A high degree of correlation between the general GRBAS and CAPE-V grades (coefficient = 0.842) was observed, with similarities in the grades of dysphonia distribution in both scales. The evaluators indicated a mild difficulty in applying the GRBAS scale and low to mild difficulty in applying the CAPE-V scale. The three evaluators agreed when indicating the GRBAS scale as the fastest and the CAPE-V scale as the most sensitive, especially for detecting small changes in voice. Conclusions. The two scales are reliable and are indicated for use in analyzing voice quality.