Update README.md

README.md

 # Recommendation system based on Tamil-English code-mixed text analysis.
 
+**Main objective **
+    *This recommendation systems provide a mechanism to assist users in classifying users with similar 
+    interests. And it will give Opportunities for users to engage with comments section to read about 
+    the movie contents, movie’s strengths, and weaknesses. So, the user will be attached with the 
+    movies with knowledge of the contents and details about films. This document focuses on the movie 
+    recommendation systems whose primary objective is to suggest a recommender system through 
+    Natural Language Processing (NLP) Tools for Tamil-English Code-mixed Comments.*
+
+
+** Individual Objectives**
+        > Sub Objective 1
+            *This includes trying to predict the natural language of a part of the comment. It is important to know 
+            the language of the text before taking any other action. This is essential for translation and 
+            sentiment analysis. Normalization aims to divide the large database table into smaller tables and 
+            link them using relationship. Avoids duplicate data or no repeating groups into a table by using 
+            Normalization. After normalization comment would convert into the Tamil English code mixed data.
+            *
+            
+        > Sub Objective 2
+            *The platform will enhance the interest of the films, decrease the time and valuable data 
+            consumption of the users for searching movies, and Tele dramas. by the sentimental analysis we can 
+            easily get knowledge about films and teledramas. there for we can decrease our searching time. by 
+            the sentimental analysis we can easily find a perfect matching movie, and also, we can lift down our 
+            data consumptions of user’s device.
+            *
+        
+        > Sub Objective 3
+        *we are all excepting an easy way of approaches while watching movies, Series, Teledramas, songs 
+        and others, but we would like to see them quick way in our real life. it can be referred by someone 
+        or we heard before about that. We are simplifying it with using this application. because let you 
+        think if our machine will give us some related suggestions of films, songs, teledramas. Yes, we can 
+        capture that movement in real by the natural language processing system. The Application will 
+        suggest you related kind of songs, films to the users.
+        *
+        
+        > Sub Objective 4
+        *users can get better understand about the movies and teledramas by the rating system. Through 
+        evaluating the rating of the past users, new users and current users will gain a better understanding 
+        of whether the past users benefited or not from such movies and teledramas. Anyone can give see 
+        ratings and feedback from the system about the films and others. So, the user does not want to 
+        afraid to use this application. We are creating a visible comment, ratings, user’s sentimental 
+        feedback and a valuable recommend contents. This will give a lot of fun and entertainment to the 
+        users.
+        *
+        
+**Research Problem**
+    1 Identification of code-mixed text
+    2 Normalizing the code-mixed text
+    3 Analyzing the  sentiment in code-mixed text
+    4 Translating the code-mixed text
+
+
+**Research Questions**
+    
+    Is the features and techniques of previous research has good result?
+    
+    How to overcome the problems in the previous project?
+    
+    What unique feature does my function have?
+    
+    How to provide low-budget system for my area?
+