Large scale multi-label text classification of a hierarchical dataset using Rocchio algorithm

Hierarchical data is becoming increasingly prominent, especially on the web. Wikipedia is one such example where there are millions of documents that are classified into multiple classes in a hierarchical fashion. This gives rise to an interesting problem of automating the classification of new documents. As the size of the dataset grows, so does the number of classes. Further, there seems to be sparsity issue even with the increase in the dataset. Therefore, this poses a challenge to classify data in such a manner. We present two different algorithms based on text categorization: Rocchio algorithm and kNN. We implement and compare the above mentioned methods to better understand the approach to take in classifying hierarchical data.