Solomon Islands Aquatic Agricultural Systems Program design document

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.

Spoken document representations for probabilistic retrieval

This paper presents some developments in query expansion and document representation of our spoken document retrieval system and shows how various retrieval techniques affect performance for different sets of transcriptions derived from a common speech source. Modifications of the document representation are used, which combine several techniques for query expansion, knowledge-based on one hand and statistics-based on the other. Taken together, these techniques can improve Average Precision by over 19% relative to a system similar to that which we presented at TREC-7. These new experiments have also confirmed that the degradation of Average Precision due to a word error rate (WER) of 25% is quite small (3.7% relative) and can be reduced to almost zero (0.2% relative). The overall improvement of the retrieval system can also be observed for seven different sets of transcriptions from different recognition engines with a WER ranging from 24.8% to 61.5%. We hope to repeat these experiments when larger document collections become available, in order to evaluate the scalability of these techniques.

Corporate document mining for technology intelligence: An analysis of needs, utilization and possibilities

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.

Analysis of document-mining techniques and tools for technology intelligence: Discovering knowledge from technical documents

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.

improving document icon to re-find efficiently what you need

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.

smoothing document language model with local word graph

ACM SIGIR; ACM SIGWEB