Knowledge discovery involves data driven processes where data is transformed and processed by various algorithms to identify new knowledge. KnowMiner is a service oriented framework providing a rich set of knowledge discovery functionalities with focus on text data sets. Complementing results of automatic machine analysis with the immense processing power of human visual apparatus has the potential of significantly improving the process of acquiring new knowledge. VisTools is a lightweight visual analytics framework based on multiple coordinated views (MCV) paradigm designed for deployment atop the KnowMiner's service architecture. In this paper we briefly present both frameworks and, driven by real-world customer requirements, describe how visual techniques can be synergistically combined with machine processing for effective analysis of dynamically changing, metadatarich text documents sets.

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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 Knowminer 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.

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