Tackling redundancy in text summarization through different levels of language analysis

One of the main challenges to be addressed in text summarization concerns the detection of redundant information. This paper presents a detailed analysis of three methods for achieving such goal. The proposed methods rely on different levels of language analysis: lexical, syntactic and semantic. Moreover, they are also analyzed for detecting relevance in texts. The results show that semantic-based methods are able to detect up to 90% of redundancy, compared to only the 19% of lexical-based ones. This is also reflected in the quality of the generated summaries, obtaining better summaries when employing syntactic- or semantic-based approaches to remove redundancy.

Environmental health, indigenous identity, cultural representations and the production of ecological consciousness in Northern Ontario

The primary goal of this research is to document local perspectives by presenting a set of commentaries and meanings, in the form of narratives, related to environmental health conceptions on an Oji-Cree reserve in Northeastern Ontario, Canada. Through an ethnographic case study, this research explores how the modern-day production of a sociocentric and ecocentric self, as ethnic marker and moral category, is contributing to environmental/community health and well-being on Native reserves. Cultural representations of personhood and community based on the Medicine Wheel model, as a cognitive model, create an ontological paradigm that promotes a holistic foundation for human behaviour and interaction, as well as healthy, sustainable communities.