This paper proposes a novel framework for mining regional colocation patterns with respect to sets of continuous variables in spatial datasets. The goal is to identify regions in ...
Christoph F. Eick, Jean-Philippe Nicot, Rachana Pa...
Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
Real-world relational data are seldom stationary, yet traditional collaborative filtering algorithms generally rely on this assumption. Motivated by our sales prediction problem, ...
Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff Schneide...
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...