title: Digital libraries for creative communities

authors: Witten, Ian H.

subjects: computer science

abstract: Digital library technologies have a great deal to offer to creative, design communities. They can enable large collections of text, images, music, video and other information objects to be organised and accessed in interesting and diverse ways. Ordinary people—people not traditionally viewed as 'creators' or 'designers'—can now conceive, assemble, build, and disseminate new information collections. This paper explores the development rationale behind the Greenstone digital library technology. We also examine three examples of creative new techniques for accessing and presenting information in digital libraries and stress the importance of tailoring information access to support the requirements of the users and application area.

text: Digital libraries for creative communities Digital library technologies have a great deal to offer to creative, design communities. They can enable large collections of text, images, music, video and other information objects to be organised and accessed in interesting and diverse ways. Ordinary people—people not traditionally viewed as 'creators' or 'designers'—can now conceive, assemble, build, and disseminate new information collections. This paper explores the development rationale behind the Greenstone digital library technology. We also examine three examples of creative new techniques for accessing and presenting information in digital libraries and stress the importance of tailoring information access to support the requirements of the users and application area.

year: 2004

title: Towards a framework for designing full model selection and optimization systems

authors: Sun, Quan

subjects: computer science

abstract: People from a variety of industrial domains are beginning to realise that appropriate use of machine learning techniques for their data mining projects could bring great benefits. End-users now have to face the new problem of how to choose a combination of data processing tools and algorithms for a given dataset. This problem is usually termed the Full Model Selection (FMS) problem. Extended from our previous work [10], in this paper, we introduce a framework for designing FMS algorithms. Under this framework, we propose a novel algorithm combining both genetic algorithms (GA) and particle swarm optimization (PSO) named GPS (which stands for GA-PSO-FMS), in which a GA is used for searching the optimal structure for a data mining solution, and PSO is used for searching optimal parameters for a particular structure instance. Given a classification dataset, GPS outputs a FMS solution as a directed acyclic graph consisting of diverse data mining operators that are available to the problem. Experimental results demonstrate the benefit of the algorithm. We also present, with detailed analysis, two model-tree-based variants for speeding up the GPS algorithm.

text: Towards a framework for designing full model selection and optimization systems People from a variety of industrial domains are beginning to realise that appropriate use of machine learning techniques for their data mining projects could bring great benefits. End-users now have to face the new problem of how to choose a combination of data processing tools and algorithms for a given dataset. This problem is usually termed the Full Model Selection (FMS) problem. Extended from our previous work [10], in this paper, we introduce a framework for designing FMS algorithms. Under this framework, we propose a novel algorithm combining both genetic algorithms (GA) and particle swarm optimization (PSO) named GPS (which stands for GA-PSO-FMS), in which a GA is used for searching the optimal structure for a data mining solution, and PSO is used for searching optimal parameters for a particular structure instance. Given a classification dataset, GPS outputs a FMS solution as a directed acyclic graph consisting of diverse data mining operators that are available to the problem. Experimental results demonstrate the benefit of the algorithm. We also present, with detailed analysis, two model-tree-based variants for speeding up the GPS algorithm.

year: 2013

title: Maori perspectives of the environment: A review of resource use consent submissions made by iwi to Environment Waikato.

authors: Whangapirita, Laura

subjects: Maori

abstract: As part of our broader brief to gather, summarise, analyse and distribute information held by Environment Waikato on Maori and the environment, we reviewed and summarised iwi consent submissions made on various resource use consent applications. This report refers to values and beliefs sourced from iwi submissions held by Environment Waikato and are presented within a Maori values framework to highlight environmental perspectives of tangata whenua in the Waikato region.

text: Maori perspectives of the environment: A review of resource use consent submissions made by iwi to Environment Waikato. As part of our broader brief to gather, summarise, analyse and distribute information held by Environment Waikato on Maori and the environment, we reviewed and summarised iwi consent submissions made on various resource use consent applications. This report refers to values and beliefs sourced from iwi submissions held by Environment Waikato and are presented within a Maori values framework to highlight environmental perspectives of tangata whenua in the Waikato region.

year: 2003-11