Visualizing Wikipedia using t SNE
This paper presents an approach on visualizing high dimensional data of Wikipedia. Visualizing data is an important and well studied problem. Visualizing highdimensional data can viewed as a dimensionality reduction problem. Over the past few decades many techniques have been proposed for linear and nonlinear dimensionality reduction. In this paper we use one such non linear dimensionality reduction technique called tDistributed Stochastic Neighbor Embedding and specifically the version using Barnes Hut algorithm for approximation. We also show that using semantic role labels as features for dimensionality reduction, we are able to visualize well clustered data with clusters containing similar data.