I've got a training DataSet and a Test DataSet. How can we experiment and get results ? Can WEKA be used for the same ?
The topic is Word Sense Disambiguation using Support Vector Machine Supervised learning Approach
The Document types within both the sets include following file types: 1. 2 XML files 2. README file 3. SENSEMAP format 4. TRAIN format 5. KEY format 6. WORDS format
Machine learning approaches like SVM are not popular with word sense disambiguation.
Are you aware of Wikify, mapping to wikipedia can be considered very fine word-sense disambiguation.
To answer your question, in cases like these; any machine learning technique can give you desired results. One should be more worried about the features to extract and make sure the word features are distinctive enough to resolve the disambiguations at the level you chose. For example in the sentence:
Wish you a very Happy Christamas
you just want to disambiguateHappy Christmas
as either book or festival.