Affective — Hierarchical classification of text — An approach using NLP toolkit

In recent years, there has been a great interest in analyzing complex text documents and corpora. Digital textual content is being increased day by day and it is very challenging to summarize all the data to be meaningful content and also to understand the relationship among the data. The objective of this experiment is to classify the terminologies based on related topics and to visualize the classified topics in the tree structure. The outcome will state the opinion, which is followed to form a sentence in laymen terms, because the average user cannot easily understand the analytical result - although there are many techniques being used for opinion mining. Initially, text acquisition will be done from corpora available in NLP toolkit (a suite of Python), and the large text corpora will be analyzed. The next step is, hierarchical topics will be classified using Fuzzy Logic and unsupervised learning method will be followed to complete this part. Finally, the visualization techniques will be applied to display the classified topics.