Recent studies have shown that over 85% of the information organizations deal with is unstructured – the vast majority of which is in text. A multitude of techniques has to be used in order to enable intelligent access to this information and to support transforming it to forms that allow sensible use of the information. While the most commonly used approach is keyword search, popularized by commercial search engines such as Google, Yahoo! and Bing, the research community has made a lot of progress moving beyond these techniques. The fundamental issue that all these advances need to address is that of semantics – there is a need to move toward understanding the text at an appropriate level, beyond the word level, in order to support access, knowledge extraction and synthesis. This paper surveys some of our research in these directions, focusing on software tools and products more than techniques; in doing that it addresses several dimensions of text understanding that can facilitate access to and extraction of knowledge from unstructured text, transforming it to forms that are useful to different users in different settings, and integrating it along multiple dimensions and with existing institutional resources.
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