The Experts below are selected from a list of 171348 Experts worldwide ranked by ideXlab platform
Lin Mao-sheng - One of the best experts on this subject based on the ideXlab platform.
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A Real-time Information Synthesis Method Based on Software Behavior
Computer Engineering, 2012Co-Authors: Lin Mao-shengAbstract:In the processes of Information Synthesis with lots of database tables,the task with Change Data Capture(CDC) settings not only is fussy,but also it can affect the efficiency.For such a problem,from the software behaviors point of view,this paper designs a real-time Information Synthesis method.The software is under monitor by constructing behavior-data mapping,through which the CDC load of database can apportion to terminal computers.Actual test result indicates that the method is no concern about the type of database,and it has good feasibility and applicability.
Maarten De Rijke - One of the best experts on this subject based on the ideXlab platform.
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CLEF - Overview of WebCLEF 2008
Lecture Notes in Computer Science, 2009Co-Authors: Valentin Jijkoun, Maarten De RijkeAbstract:We describe the WebCLEF 2008 task. Similarly to the 2007 edition of WebCLEF, the 2008 edition implements a multilingual "Information Synthesis" task, where, for a given topic, participating systems have to extract important snippets from web pages. We detail the task, the assessment procedure, the evaluation measures and results.
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CLEF (Working Notes) - Overview of WebCLEF 2008 (Draft)
2008Co-Authors: Valentin Jijkoun, Maarten De RijkeAbstract:We describe the WebCLEF 2008 task. Similarly to the 2007 edition of WebCLEF, the 2008 edition implements a multilingual \Information Synthesis" task, where, for a given topic, participating systems have to extract important snippets from web pages. We detail the task and the assessment procedure. At the time of writing evaluation results are not available yet.
Valentin Jijkoun - One of the best experts on this subject based on the ideXlab platform.
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CLEF - Overview of WebCLEF 2008
Lecture Notes in Computer Science, 2009Co-Authors: Valentin Jijkoun, Maarten De RijkeAbstract:We describe the WebCLEF 2008 task. Similarly to the 2007 edition of WebCLEF, the 2008 edition implements a multilingual "Information Synthesis" task, where, for a given topic, participating systems have to extract important snippets from web pages. We detail the task, the assessment procedure, the evaluation measures and results.
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CLEF (Working Notes) - Overview of WebCLEF 2008 (Draft)
2008Co-Authors: Valentin Jijkoun, Maarten De RijkeAbstract:We describe the WebCLEF 2008 task. Similarly to the 2007 edition of WebCLEF, the 2008 edition implements a multilingual \Information Synthesis" task, where, for a given topic, participating systems have to extract important snippets from web pages. We detail the task and the assessment procedure. At the time of writing evaluation results are not available yet.
Wanda Pratt - One of the best experts on this subject based on the ideXlab platform.
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collaborative Information Synthesis i a model of Information behaviors of scientists in medicine and public health
Journal of the Association for Information Science and Technology, 2006Co-Authors: Catherine Blake, Wanda PrattAbstract:Scientists engage in the discovery process more than any other user population, yet their day-to-day activities are often elusive. One activity that consumes much of a scientist's time is developing models that balance contradictory and redundant evidence. Driven by our desire to understand the Information behaviors of this important user group, and the behaviors of scientific discovery in general, we conducted an observational study of academic research scientists as they resolved different experimental results reported in the biomedical literature. This article is the first of two that reports our findings. In this article, we introduce the Collaborative Information Synthesis (CIS) model that reflects the salient Information behaviors that we observed. The CIS model emerges from a rich collection of qualitative data including interviews, electronic recordings of meetings, meeting minutes, e-mail communications, and extraction worksheets. Our findings suggest that scientists provide two Information constructs: a hypothesis projection and context Information. They also engage in four critical tasks: retrieval, extraction, verification, and analysis. The findings also suggest that science is not an individual but rather a collaborative activity and that scientists use the results of one analysis to inform new analyses. In Part 2, we compare and contrast existing Information and cognitive models that have inadvertently reported Synthesis, and then provide five recommendations that will enable designers to build Information systems that support the important Synthesis activity. © 2006 Wiley Periodicals, Inc.
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ASIST - Collaborative Information Synthesis
Proceedings of the American Society for Information Science and Technology, 2005Co-Authors: Catherine Blake, Wanda PrattAbstract:As the quantity of scientific literature continues to soar, scientists struggle to keep up with new findings, even in narrow areas of expertise. Although advances in Information retrieval have eased the task of finding relevant articles, scientists now must face the challenge of aggregating Information from within the retrieved set of documents. Our study explores the user behavior and Information requirements of scientists as they interact with medical literature to answer research questions. We found that although their Information needs were clearly defined, they still refined the retrieval, extraction, and analysis phases of a process that we have called Information Synthesis. We also found that they actively collaborated throughout the process. We describe their behavior and introduce our design and progress twoards our tool METIS (Multi-user ExTraction and Information Synthesis) that will support the collaborative Information Synthesis process used by public health and biomedical scientists.
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Information Synthesis: a mixed-initiative meta-analytic approach to facilitate knowledge discovery from scientific text
2003Co-Authors: Catherine Blake, Dennis F. Kibler, Wanda PrattAbstract:The quantities of electronic Information resources continue to increase at an overwhelming rate. Although retrieval systems have eased the task of collecting articles, users struggle to incorporate new findings into their work practices and have few opportunities to explore implicit connections within a collection of Information resources. My goal is to develop methodologies and associated technologies that will facilitate discovery from textual Information resources. Inspired by my study of users in medicine and public health as they synthesized evidence from literature, I introduce a new process called Information Synthesis. I designed the Information Synthesis process for users who make consequential decisions and who operate in an intensive environment. The process increases a user's opportunity to detect novel phenomena by incorporating typically unused Information from scientific articles. I developed the M ulti-user Extraction for Information Synthesis ( METIS) system to demonstrate the feasibility of the Information Synthesis approach. METIS automates critical tasks within the Information Synthesis process which are to (1) identify Information from full-text articles, (2) estimate a comparison group using the extracted Information as an index to an external database, and (3) compare the facts reported in each article with the comparison group using a meta-analytic technique. The METIS generated quantitative and visual summaries reflect the redundancies and contradictions that are inevitable in an Information intensive environment. I make three claims regarding the METIS system: (1) the shallow natural language processing used within the METIS Information extractor identify Information items at a level of precision and recall that are consistent with current state of the art; (2) the METIS comparison estimator estimates a comparison group rate that is similar to the rates found in a traditional analysis; and (3) the METIS analyzer produces the same effect size as published analyses. I evaluated the Information Synthesis empirically by exploring risk factors within a corpus of breast cancer articles. My results show that the Information Synthesis approach was (1) more comprehensive than existing published analyses that explored a similar hypothesis projection, and (2) able to identify phenomena that existing Synthesis techniques were unable to detect.
Meng Yang - One of the best experts on this subject based on the ideXlab platform.
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Sample-Based Vegetation Distribution Information Synthesis.
PloS one, 2015Co-Authors: Gang Yang, Meng YangAbstract:In constructing and visualizing a virtual three-dimensional forest scene, we must first obtain the vegetation distribution, namely, the location of each plant in the forest. Because the forest contains a large number of plants, the distribution of each plant is difficult to obtain from actual measurement methods. Random approaches are used as common solutions to simulate a forest distribution but fail to reflect the specific biological arrangements among types of plants. Observations show that plants in the forest tend to generate particular distribution patterns due to growth competition and specific habitats. This pattern, which represents a local feature in the distribution and occurs repeatedly in the forest, is in line with the “locality” and “static” characteristics in the “texture data”, making it possible to use a sample-based texture Synthesis strategy to build the distribution. We propose a vegetation distribution data generation method that uses sample-based vector pattern Synthesis. A sample forest stand is obtained first and recorded as a two-dimensional vector-element distribution pattern. Next, the large-scale vegetation distribution pattern is synthesized automatically using the proposed vector pattern Synthesis algorithm. The synthesized distribution pattern resembles the sample pattern in the distribution features. The vector pattern Synthesis algorithm proposed in this paper adopts a neighborhood comparison technique based on histogram matching, which makes it efficient and easy to implement. Experiments show that the distribution pattern synthesized with this method can sufficiently preserve the features of the sample distribution pattern, making our method meaningful for constructing realistic forest scenes.