Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Extractive summarization using complex networks and syntactic dependency

The realization that statistical physics methods can be applied to analyze written texts represented as complex networks has led to several developments in natural language processing, including automatic summarization and evaluation of machine translation. Most importantly, so far only a few metrics of complex networks have been used and therefore there is ample opportunity to enhance the statistics-based methods as new measures of network topology and dynamics are created. In this paper, we employ for the first time the metrics betweenness, vulnerability and diversity to analyze written texts in Brazilian Portuguese. Using strategies based on diversity metrics, a better performance in automatic summarization is achieved in comparison to previous work employing complex networks. With an optimized method the Rouge score (an automatic evaluation method used in summarization) was 0.5089, which is the best value ever achieved for an extractive summarizer with statistical methods based on complex networks for Brazilian Portuguese. Furthermore, the diversity metric can detect keywords with high precision, which is why we believe it is suitable to produce good summaries. It is also shown that incorporating linguistic knowledge through a syntactic parser does enhance the performance of the automatic summarizers, as expected, but the increase in the Rouge score is only minor. These results reinforce the suitability of complex network methods for improving automatic summarizers in particular, and treating text in general. (C) 2011 Elsevier B.V. All rights reserved.

Directions for advancing the study of work transitions in the 21st century

Objectives: The purpose of this article is to share the details, outcomes and deliverables from an international workshop on work transitions in London, Ontario, Canada. Participants: Researchers, graduate students, and community group members met to identity ways to advance the knowledge base of strategies to enhance work participation for those in the most disadvantaged groups within society. Methods: A participatory approach was used in this workshop with presentations by researchers and graduate students. This approach included dialogue and discussion with community members. In addition, small group dialogue and debate, world cafe discussions, written summaries of group discussion and reflection boards were used to bring new ideas to the discussion and to build upon what we know. Findings: Two research imperatives and six research recommendations were identified to advance global dialogue on work transitions and to advance the knowledge base. Occupational justice can be used to support future research directions in the study of work transitions. Conclusions: Moving forward requires a commitment of community of researchers, clinicians and stakeholders to address work disparities and implement solutions to promote participation in work.

Inconsistent-tolerant base revision through Argument Theory Change

Reasoning and change over inconsistent knowledge bases (KBs) is of utmost relevance in areas like medicine and law. Argumentation may bring the possibility to cope with both problems. Firstly, by constructing an argumentation framework (AF) from the inconsistent KB, we can decide whether to accept or reject a certain claim through the interplay among arguments and counterarguments. Secondly, by handling dynamics of arguments of the AF, we might deal with the dynamics of knowledge of the underlying inconsistent KB. Dynamics of arguments has recently attracted attention and although some approaches have been proposed, a full axiomatization within the theory of belief revision was still missing. A revision arises when we want the argumentation semantics to accept an argument. Argument Theory Change (ATC) encloses the revision operators that modify the AF by analyzing dialectical trees-arguments as nodes and attacks as edges-as the adopted argumentation semantics. In this article, we present a simple approach to ATC based on propositional KBs. This allows to manage change of inconsistent KBs by relying upon classical belief revision, although contrary to it, consistency restoration of the KB is avoided. Subsequently, a set of rationality postulates adapted to argumentation is given, and finally, the proposed model of change is related to the postulates through the corresponding representation theorem. Though we focus on propositional logic, the results can be easily extended to more expressive formalisms such as first-order logic and description logics, to handle evolution of ontologies.

Environmental assessment of residues generated after consecutive acid-base pretreatment of sugarcane bagasse by advanced oxidative process

Abstract Background Biofuels produced from sugarcane bagasse (SB) have shown promising results as a suitable alternative of gasoline. Biofuels provide unique, strategic, environmental and socio-economic benefits. However, production of biofuels from SB has negative impact on environment due to the use of harsh chemicals during pretreatment. Consecutive sulfuric acid-sodium hydroxide pretreatment of SB is an effective process which eventually ameliorates the accessibility of cellulase towards cellulose for the sugars production. Alkaline hydrolysate of SB is black liquor containing high amount of dissolved lignin. Results This work evaluates the environmental impact of residues generated during the consecutive acid-base pretreatment of SB. Advanced oxidative process (AOP) was used based on photo-Fenton reaction mechanism (Fenton Reagent/UV). Experiments were performed in batch mode following factorial design L9 (Taguchi orthogonal array design of experiments), considering the three operation variables: temperature (°C), pH, Fenton Reagent (Fe2+/H2O2) + ultraviolet. Reduction of total phenolics (TP) and total organic carbon (TOC) were responsive variables. Among the tested conditions, experiment 7 (temperature, 35°C; pH, 2.5; Fenton reagent, 144 ml H2O2+153 ml Fe2+; UV, 16W) revealed the maximum reduction in TP (98.65%) and TOC (95.73%). Parameters such as chemical oxygen demand (COD), biochemical oxygen demand (BOD), BOD/COD ratio, color intensity and turbidity also showed a significant change in AOP mediated lignin solution than the native alkaline hydrolysate. Conclusion AOP based on Fenton Reagent/UV reaction mechanism showed efficient removal of TP and TOC from sugarcane bagasse alkaline hydrolysate (lignin solution). To the best of our knowledge, this is the first report on statistical optimization of the removal of TP and TOC from sugarcane bagasse alkaline hydrolysate employing Fenton reagent mediated AOP process.