Maestro Algorithm for Sentiment Evaluation

Opinion mining is very powerful technique in Information discovery in a vast set of structured and unstructured data. One of extremely useful application can be, to extract the qualities of a student from the Letter of Recommendation written by the professors of college. The extracted information is an instrument to judge the student's personality based on the different capabilities of a student. To execute the application, an efficient algorithm is required. Which can analyze the syntax of a sentence and further assign appropriate weights to each required piece of information. In the paper we have proposed "Maestro Algorithm" which has been designed after extensive research on syntax behavior of sentences in English grammar. The weights in the algorithm have been assigned based on a survey conducted on sixty teachers. The survey was conducted to evaluate the opinion of the teachers, regarding what attributes contribute to the personality of the student. The survey revealed five key categories along with percentages. Accordingly, maestro algorithm analyzes each and every sentence and extract the required information. Further it categorizes the extracted information and form the "estrella structure" after applying the proposed equations in the paper. The "estrella structure" is the final opinionated result of the algorithm.