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Knowminer Search - A Multi-visualisation Collaborative Approach to Search Result Analysis

机译:知识人员搜索 - 一种用于搜索结果分析的多可视化协作方法

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The amount of information available on the internet and within enterprises has reached an incredible dimension. Efficiently finding and understanding information and thereby saving resources remains one of the major challenges in our daily work. Powerful text analysis methods, a scalable faceted retrieval engine and a well-designed interactive user interface are required to address the problem. Besides providing means for drilling-down to the relevant piece of information, a part of the challenge arises from the need of analysing and visualising data to discover relationships and correlations, gain an overview of data distributions and unveil trends. Visual interfaces leverage the enormous bandwidth of the human visual system to support pattern discovery in large amounts of data. Our Know miner search builds upon the well-known faceted search approach which is extended with interactive visualisations allowing users to analyse different aspects of the result set. Additionally, our system provides functionality for organising interesting search results into portfolios, and also supports social features for rating and boosting search results and for sharing and annotating portfolios.
机译:互联网和企业内提供的信息量已达到令人难以置信的维度。有效地发现和理解信息,从而节省资源仍然是我们日常工作中的主要挑战之一。强大的文本分析方法,可伸缩的刻面检索引擎和精心设计的交互式用户界面来解决问题。除了为钻井到相关信息的手段之外,一部分挑战是由于需要分析和可视化数据来发现关系和相关性,并概述数据分布和揭示趋势。可视接口利用人类视觉系统的巨大带宽来支持大量数据的模式发现。我们知道矿工搜索在众所周知的面位搜索方法上构建,该方法与交互式的可视化扩展,允许用户分析结果集的不同方面。此外,我们的系统提供了将有趣的搜索结果组织到投资组合中的功能,并支持社交功能,以便评级和提高搜索结果以及共享和注释投资组合。

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