Improving Image Clustering using Sparse Text and the Wisdom of the Crowds
Anna Ma, Arjuna Flenner, Deanna Needell, Allon G. Percus
We propose a method to improve image clustering using sparse text and the wisdom of the crowds. In particular, we present a method to fuse two different kinds of document features, image and text features, and use a common dictionary or "wisdom of the crowds" as the connection between the two different kinds of documents. With the proposed fusion matrix, we use topic modeling via non-negative matrix factorization to cluster documents.
cs.LG, cs.CV