An Innovative Approach for Text Document Identification through Word Clouds technique

Text is a versatile and valuable approach to conveying information and knowledge. Unstructured data, however, poses challenges when it comes to reading and extracting valuable information. Users cannot find their subject domains within a matter of seconds without reading them at all. To accurately determine the category of a document or text data, the user must identify the presence of certain key sections in the document. So, text analysis is required to get hidden features from data. Word cloud is one of the important tools in machine learning useful for summarizing and visualizing important words and themes. It can extract relevant features necessary for categorizing text documents into appropriate themes. In this study, we use a document identification approach based on word clouds. Present study uses various news for identification purpose which were downloaded from different newspaper websites. People can find their topics in seconds without even reading them. This study provides numerous interactive graphics and robust, customizable features to help understand the subject of a document.