Page 31 - Demo

%u062c%u0645%u064a%u0639 %u0627%u0644%u062d%u0642%u0648%u0642 %u0645%u062d%u0641%u0648%u0638%u0629 %u0640 %u0627%u0625%u0644%u0639%u062a%u062f%u0627%u0621 %u0639%u0649%u0644 %u062d%u0642 %u0627%u0645%u0644%u0624%u0644%u0641 %u0628%u0627%u0644%u0646%u0633%u062e %u0623%u0648 %u0627%u0644%u0637%u0628%u0627%u0639%u0629 %u064a%u0639%u0631%u0636 %u0641%u0627%u0639%u0644%u0647 %u0644%u0644%u0645%u0633%u0627%u0626%u0644%u0629 %u0627%u0644%u0642%u0627%u0646%u0648%u0646%u064a%u062931 Visualizing complex data and relations for text and social networks is done with Tag and word clouds. The importance of tag/word is represented by font size/color, Besides text data, there are also methods to visualize relationships, such as visualizing social networks VI. Measuring Data Similarity and Dissimilarity Similarity is a numerical measure of how alike two data objects are,Its value is higher when objects are more alike,often falls in the range [0,1 ] Dissimilarity (distance) is a numerical measure of how different two data objects are, its value lower when objects are more alike, minimum dissimilarity is often 0, upper limit varies The term Proximity refers to a similarity or dissimilarity. Data matrix (or object-by-attribute structure): This structure stores the n data objects in the form of a relational table, or n-by-p matrix (n objects %u00d7p attributes): x11...xi1... ...............x1f... xif...xnf...............x1p... xip ... xnp