Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
New applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasets structured as graphs. We present an efficient algorithm for minin...
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Computational finance leverages computer technologies to build models from large amounts of data to extract insight. In today's networked world, the amount of data available t...
Badrish Chandramouli, Mohamed H. Ali, Jonathan Gol...