Use various add-ons available within Orange to mine data from external data sources, perform natural language processing and text mining, conduct network analysis, infer frequent itemset and do association rules mining. Additionally, bioinformaticians and molecular biologists can use Orange to rank genes by their differential expression and perform enrichment analysis.
Table 1: Text Mining and Text Analytics Linguistic and statistical approaches for processing text provide complementary results for extracting value from unstructured textual data. Though each has been practiced independently, the most effective solutions combine their strengths. This balances the precision of linguistically based text analytics with the powerful recall of a statistical text mining approach. The rapid growth of "big data" and predictive analytics means that the best techniques for achieving this balance will be constantly evolving, yet the tools exist today to make great progress on the wide variety of textual analytics challenges.
Text-mining software is one of the front-line tools that the government is now using to tease out valuable connections. These specialized search engines can quickly sift through mountains of unstructured text anything that's not carefully arranged in a database or spreadsheet and pull out the meaningful stuff. They can infer relationships within data that are not stated explicitly. It is something we do all the time automatically but is enormously complicated for computers. "We bridge the gap between information and action," says Barak Pridor, CEO of ClearForest, a text-mining company.
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