Short text classification based on semi supervised learning
With the rapid development of world wide web,there are more and more short texts emerging on the Web,such as abstract of paper,twitter and email.They are short,keeping links with each other,and there are only a small set of labeled instances available.For the sake of classifying the short text,we present a new method named semi supervised learning based iterative classification algorithm(SS ICA),which has the ability to classify the instances with a small set of labeled instances iteratively.Experiment indicates that SS ICA significantly increases accuracy when compared to other traditional methods on small training set.