945 resultados para DOCUMENT COLLECTIONS


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This is the River Teign Salmon Action Plan Consultation document produced by the Environment Agency in 2003. The report pays attention on the external consultation of the River Teign Salmon Action Plan (SAP). This approach to salmon management within the England and Wales introduces the concept of river-specific Conservation Limits as a method of assessing the status of the salmon stock. The River Teign Salmon Action Plan follows the format of those completed for the Rivers Torridge, Taw and Dart. It is the fourth of eight action plans that will be produced for salmon rivers within the Devon Area Fisheries, Recreation and Biodiversity Team. The River Teign SAP contains a description of the river catchment and highlights particular features that are relevant to the salmon population and the associated fishery. The Teign salmon stock is currently failing to meet its conservation limit. This failure is largely attributed to the reduction in the survival rate during the marine phase of the salmon life cycle. This is likely to constrain stocks to lower levels than have existed historically. Still further catch controls may contribute to a reduction in exploitation rates and allow stocks to recover to meet their conservation limit. Other important actions include the continuation of habitat improvement works which aim to maximise spawning habitat utilisation, spawning success, and juvenile survival and production.

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WorldFish is leading the CGIAR Research Program on Aquatic Agricultural Systems together with two other CGIAR Centers; the International Water Management Institute (IWMI) and Bioversity. In 2012 and 2013 the AAS Program rolled out in Solomon Islands, Zambia, Bangladesh, Cambodia and the Philippines. Aquatic Agricultural Systems are places where farming and fishing in freshwater and/or coastal ecosystems contribute significantly to household income and food security. The program goal is to improve the well-being of AAS-dependent people. A hub is a geographic location that provides a focus for learning, innovation and impact through participatory action research. In Solomon Islands AAS works in Malaita Hub (Malaita Province) and Western Hub (Western Province). In each hub we identify a ‘Development Challenge’ that the Program will address to give us focus and motivation.

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This paper focuses on document data, one of the most significant sources for technology intelligence. To help organisations use their knowledge in documents effectively, this research aims to identify what organizations really want from documents and what might be possible to obtain from them. The research involves a literature review, a series of in-depth/on-site interviews and a descriptive analysis of document mining applications. The output of the research includes: a document mining framework; an analysis of the current condition of document mining in technology-based organisations together with their future requirements; and guidelines for introducing document mining into an organisation along with a discussion on the practical issues that are faced by users. Copyright © 2011 Inderscience Enterprises Ltd.

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This research proposes a method for extracting technology intelligence (TI) systematically from a large set of document data. To do this, the internal and external sources in the form of documents, which might be valuable for TI, are first identified. Then the existing techniques and software systems applicable to document analysis are examined. Finally, based on the reviews, a document-mining framework designed for TI is suggested and guidelines for software selection are proposed. The research output is expected to support intelligence operatives in finding suitable techniques and software systems for getting value from document-mining and thus facilitate effective knowledge management. Copyright © 2012 Inderscience Enterprises Ltd.

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Abstract. Latent Dirichlet Allocation (LDA) is a document level language model. In general, LDA employ the symmetry Dirichlet distribution as prior of the topic-words’ distributions to implement model smoothing. In this paper, we propose a data-driven smoothing strategy in which probability mass is allocated from smoothing-data to latent variables by the intrinsic inference procedure of LDA. In such a way, the arbitrariness of choosing latent variables'priors for the multi-level graphical model is overcome. Following this data-driven strategy,two concrete methods, Laplacian smoothing and Jelinek-Mercer smoothing, are employed to LDA model. Evaluations on different text categorization collections show data-driven smoothing can significantly improve the performance in balanced and unbalanced corpora.

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It is common that documents are represented by document icon in graphical user interfaces. The document icon facilitates user to retrieve documents, but it is difficult to distinguish the document from a collection of documents that user have accessed to. Our paper presents a document icon on which the users can add some subjective values and mark. Then we describe a system ex-explorer that users can browser and search the extent document icon. We found that it is easy to re-find the document on which users added some annotation or mark by themselves.

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ACM SIGIR; ACM SIGWEB