SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
| Hi-index | 0.00 |
In this article we describe our experiences in building the winning system for KDD Cup, 2003, Task 1. This year's competition was based on a very large archive of research papers that provides an unusually comprehensive snapshot of a particular social network in action; in addition to the full text of research papers, it includes both explicit citation structure and partial data on the downloading of papers by users. It provides a framework for testing general network and usage mining techniques, which can be explored via four varied and interesting tasks. Each task is a separate competition with its own specific goal. In task 1 the goal is to predict the change in number of citations to each paper in the archive over time.The contest was very challenging because the given data was not in a format suitable for conventional data mining techniques. So we had to do a considerable amount of data processing. Also there were different sources of data like tex files, citation graph, slac-data database. So we had to make a decision about which sources to use and how much to use.