Statistics eXplorer accessible for education and research

From: http://ncva.itn.liu.se/explorer?l=en

Statistics eXplorer integrates many common InfoVis and GeoVis methods required to make sense of statistical data, uncover patterns of interests, gain insight, tell-a-story and finally communicate knowledge. Statistics eXplorer was developed based on a component architecture and includes a wide range of visualization techniques enhanced with various interaction techniques and interactive features to support better data exploration and analysis. It also supports multiple linked views and a snapshot mechanism for capturing discoveries made during the exploratory data analysis process which can be used for sharing gained knowledge.



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Text Mining: The Next Data Frontier - Scientific Computing

From: http://www.scientificcomputing.com/articles/2014/01/text-mining-next-data-frontier#.UswIHNLuLTo

Mon, 01/06/2014 - 2:04pm
Mark Anawis

By some estimates, 80 percent of available information occurs as free-form text

Text Mining: The Next Data Frontier

Figure 1: Text Mining and Related Fields

Josiah Stamp said: “The individual source of the statistics may easily be the weakest link.” Nowhere is this more true than in the new field of text mining, given the wide variety of textual information. By some estimates, 80 percent of the information available occurs as free-form text which, prior to the development of text mining, needed to be read in its entirety in order for information to be obtained from it. It has been applied to spam filters, fraud detection, sentiment analysis, identification of trends and authorship.

Text mining can be defined as the analysis of semi-structured or unstructured text data. The goal is to turn text information into numbers so that data mining algorithms can be applied. It arose from the related fields of data mining, artificial intelligence, statistics, databases, library science, and linguistics (Figure 1).

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