Abstract: A self learning system and a method for categorizing input data have been disclosed. The system includes a generator that generates an initial training set comprising a plurality of words linked to scores/ratings which are based on the sentiments conveyed by the words. The words and corresponding ratings and sentiments are inter-linked and stored in a repository. A rule based classifier segregates the input data into individual words, and compares the words with the entries in the repository, and subsequently determines a first score corresponding to the input data. The input data is also provided to a machine-learning based classifier that generates a plurality of features corresponding to the input data and subsequently generates a second score corresponding to the input data. The first score and the second score are further aggregated by an ensemble classifier which further generates a classification score which enables the data to be classified into a plurality of predetermined categories.

Abstract: A self learning system and a method for analyzing the sentiments conveyed by an input text have been disclosed. The system includes a generator that generates an initial training set comprising a plurality of words linked to corresponding sentiments. The words and corresponding sentiments are stored in a repository. A rule based classifier segregates the input text into individual words, and compares the words with the entries in the repository, and subsequently determines a first score corresponding to the input text. The input text is also provided to a machine-learning based classifier that generates a plurality of features corresponding to the input text and subsequently generates a second score corresponding to the input text. The first score and the second score are further aggregated by an ensemble classifier which further generates a classification score indicative of the sentiment conveyed by the input text.