ADDING THIS LINE TO TEST
- Install Anaconda 2.7
- install brown corpus,wordnet, punkt modules of nltk as below
- nltk.download('punkt')
- nltk.download('brown')
- nltk.download('wordnet')
- browse your training dataset file
- training dataset should contain tab seperated sentences with its actual value at the end.
- Create directory with same name as training dataset file and place a file named 'actual.txt' in it.
- press all the buttons on by one to create that features.
- press combineall for creating csv file combining all features.
- now generate model. Note: you should create a directory 'models' where the training dataset exists.
- input two sentences and press find desgree of equivalence.
- the screen will display the degree ranging from 0 to 5.