Information mining is a mature know-how. The prediction challenge, trying to find predictive styles in info, has been broadly studied. powerful me- ods can be found to the practitioner. those tools procedure dependent numerical details, the place uniform measurements are taken over a pattern of information. textual content is frequently defined as unstructured info. So, it is going to look, textual content and numerical facts are diversified, requiring diverse tools. Or are they? In our view, a prediction challenge could be solved by means of an identical equipment, even if the knowledge are established - merical measurements or unstructured textual content. textual content and records could be reworked into measured values, corresponding to the presence or absence of phrases, and an analogous equipment that experience confirmed winning for pred- tive information mining may be utilized to textual content. but, there are key ameliorations. overview suggestions has to be tailored to the chronological order of ebook and to substitute measures of blunders. as the facts are records, extra really expert analytical tools will be most well liked for textual content. in addition, the equipment needs to be modi?ed to deal with very excessive dimensions: tens of hundreds of thousands of phrases and files. nonetheless, the significant subject matters are comparable.
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