Subjects Extraction and text data classification by CHERNOFF algorithm and implementation with Java general-purpose computer programming language

The ability of the human brain to classify new stimuli as equivalent to stimuli previously found and categorized, allows theindividual to impose order into her/his environment. Without the ability to categorize, the individual would not interactmeaningfully with the infinitely diverse number of objects and situations s/he is exposed to and, in fact, life would bechaotic. Secondly, it is cognitively advantageous and economical since it allows one to organize the infinite number ofobjects and events encountered through life into manageable easily accessible categories. But this meaning fully ofenvironment should transfer by data to the human. A data type we use to reveal preferences and goals through recruitingmaterials, magazines, and public statements, notes is using text data type. In the age of Information technology (21 century),categorizing and classification of this data family in this huge amount, costs so much. Automated text analysis methods cansubstantially reduce the costs and time of analyzing massive collections of texts, also understanding the results may beanother problem that is solved with data visualization; Data visualization is going to change the way our analysts work withdata. They’re going to be expected to respond to issues more rapidly. And they’ll need to be able to dig for more insights –look at data differently, more imaginatively. Data visualization will promote that creative data exploration. Below is aninstance for data visualization with Chernoff face algorithm, you can see how is easy now to find out the result, with thissimple visualization algorithm.

کلیدواژه ها:

Text-mining ، Subject extraction ، Chernoff face algorithm