title: Text categorization using compression models

authors: Frank, Eibe

abstract: Summary form only given. Test categorization is the assignment of natural language texts to predefined categories based on their concept. The use of predefined categories implies a "supervised learning" approach to categorization, where already-classified articles which effectively define the categories are used as "training data" to build a model that can be used for classifying new articles that comprise "the data". Typical approaches extract features from articles and use the feature vectors as input to a machine learning scheme that learns how to classify articles. The features are generally words. It has often been observed that compression seems to provide a very promising alternative approach to categorization. The overall compression of an article with respect to different models can be compared to see which one it fits most closely. Such a scheme has several potential advantages: it yields an overall judgement on the document as a whole, rather than discarding information by pre-selecting features it avoids the messy and rather artificial problem of defining word boundaries; it deals uniformly with morphological variants of words; depending on the model (and its order), it can take account of phrasal effects that span word boundaries; it offers a uniform way of dealing with different types of documents for example, arbitrary files in a computer system; it generally minimizes arbitrary decisions that inevitably need to be taken to render any learning scheme practical.

text: Text categorization using compression models Summary form only given. Test categorization is the assignment of natural language texts to predefined categories based on their concept. The use of predefined categories implies a "supervised learning" approach to categorization, where already-classified articles which effectively define the categories are used as "training data" to build a model that can be used for classifying new articles that comprise "the data". Typical approaches extract features from articles and use the feature vectors as input to a machine learning scheme that learns how to classify articles. The features are generally words. It has often been observed that compression seems to provide a very promising alternative approach to categorization. The overall compression of an article with respect to different models can be compared to see which one it fits most closely. Such a scheme has several potential advantages: it yields an overall judgement on the document as a whole, rather than discarding information by pre-selecting features it avoids the messy and rather artificial problem of defining word boundaries; it deals uniformly with morphological variants of words; depending on the model (and its order), it can take account of phrasal effects that span word boundaries; it offers a uniform way of dealing with different types of documents for example, arbitrary files in a computer system; it generally minimizes arbitrary decisions that inevitably need to be taken to render any learning scheme practical.

year: 2000-03

title: Spatial risk-based assessments for climate adaptation using the SimCLIM modelling system: a case study of domestic rainwater harvesting as the sole source of water

authors: Warrick, R.

subjects: adaptation

abstract: This paper describes a software modelling system, SimCLIM, for simulating the effects of climate variability and change, and demonstrates its application to domestic rainwater harvesting (RWH). The paper first describes SimCLIM and then focuses on a case study of the reliability of domestic RWH systems as the sole source of water in South East Queensland, a region of high spatial and temporal variability in rainfall. Using the SimCLIM scenario generator along with gridded daily time-series data and a domestic water tank model, 'risk landscapes' are created based on the risk of failure of the domestic systems to provide water under both current climate and scenarios of future change. Steep risk gradients were found, with major implications for RWH system configuration. Simulations are then performed in order to examine the trade-offs between two broad strategies - increasing runoff area and increasing tank size - required to maintain a reliable system. The paper concludes that, instead of set specifications, location-specific customisation of RWH systems is preferable in order to ensure reliability under current rainfall variability and sustainability over the long term under climate change. The availability of gridded daily rainfall datasets along with modelling tools like SimCLIM makes this customisation practicable.

text: Spatial risk-based assessments for climate adaptation using the SimCLIM modelling system: a case study of domestic rainwater harvesting as the sole source of water This paper describes a software modelling system, SimCLIM, for simulating the effects of climate variability and change, and demonstrates its application to domestic rainwater harvesting (RWH). The paper first describes SimCLIM and then focuses on a case study of the reliability of domestic RWH systems as the sole source of water in South East Queensland, a region of high spatial and temporal variability in rainfall. Using the SimCLIM scenario generator along with gridded daily time-series data and a domestic water tank model, 'risk landscapes' are created based on the risk of failure of the domestic systems to provide water under both current climate and scenarios of future change. Steep risk gradients were found, with major implications for RWH system configuration. Simulations are then performed in order to examine the trade-offs between two broad strategies - increasing runoff area and increasing tank size - required to maintain a reliable system. The paper concludes that, instead of set specifications, location-specific customisation of RWH systems is preferable in order to ensure reliability under current rainfall variability and sustainability over the long term under climate change. The availability of gridded daily rainfall datasets along with modelling tools like SimCLIM makes this customisation practicable.

year: 2012

title: Wāhine Māori engagement with literacies

authors: Masters-Awatere, Bridgette

subjects: Literacy

abstract: Wāhine Māori engagement with literacies (2023) is a case study report in collaboration with Te Whakaruruhau. It has been undertaken as part of a larger project, The expression, experience and transcendence of low skills in Aotearoa New Zealand (2019–2024), the aim of which is to provide policy recommendations to improve life-course trajectories and socio-economic outcomes for adults with low literacy and numeracy skills in Aotearoa New Zealand. Broadly speaking, Wāhine Māori engagement with literacy examines the framing and application of literacy measures in contemporary New Zealand culture. More specifically, it is about the lives and learning of wāhine (women) Māori (the indigenous peoples of Aotearoa New Zealand) within that culture and their attitudes towards, and complex relationships with, literacy as it is defined in their own lives and in the current setting. The study aims for a holistic understanding of lived literacies in driving the development of educational policies by public institutions and private groups. Reframing literacy as literacies is posited as a means to empower marginalised groups and to challenge the dominance of the Eurocentric education paradigm. Formal learning in English-language schools cannot be the extent of national literacy standards as it disregards Māori epistemological and ontological realities and can discount wāhine, many of whom may prioritise other modes of literacy. Centring their perspectives will bring about a more culturally inclusive future, one that makes space for the development of emotional and cultural literacies—as well as other forms such as digital, media, visual, financial, and health literacies—alongside the conventional version of literacy that has a monopoly in the present system.

text: Wāhine Māori engagement with literacies Wāhine Māori engagement with literacies (2023) is a case study report in collaboration with Te Whakaruruhau. It has been undertaken as part of a larger project, The expression, experience and transcendence of low skills in Aotearoa New Zealand (2019–2024), the aim of which is to provide policy recommendations to improve life-course trajectories and socio-economic outcomes for adults with low literacy and numeracy skills in Aotearoa New Zealand. Broadly speaking, Wāhine Māori engagement with literacy examines the framing and application of literacy measures in contemporary New Zealand culture. More specifically, it is about the lives and learning of wāhine (women) Māori (the indigenous peoples of Aotearoa New Zealand) within that culture and their attitudes towards, and complex relationships with, literacy as it is defined in their own lives and in the current setting. The study aims for a holistic understanding of lived literacies in driving the development of educational policies by public institutions and private groups. Reframing literacy as literacies is posited as a means to empower marginalised groups and to challenge the dominance of the Eurocentric education paradigm. Formal learning in English-language schools cannot be the extent of national literacy standards as it disregards Māori epistemological and ontological realities and can discount wāhine, many of whom may prioritise other modes of literacy. Centring their perspectives will bring about a more culturally inclusive future, one that makes space for the development of emotional and cultural literacies—as well as other forms such as digital, media, visual, financial, and health literacies—alongside the conventional version of literacy that has a monopoly in the present system.

year: 2023-09-28