Mining Efficient Taxi Operation Strategies From Large Scale Geo-Location Data

Efficient Data Mining from Large Text Databases

An Efficient Data Replication Strategy in Large-Scale Data Grid Environments Based on Availability and Popularity

The data grid technology, which uses the scale of the Internet to solve storage limitation for the huge amount of data, has become one of the hot research topics. Recently, data replication strategies have been widely employed in distributed environment to copy frequently accessed data in suitable sites. The primary purposes are shortening distance of file transmission and achieving files from ...

Efficient Model Selection for Large-Scale Nearest-Neighbor Data Mining

One of the most widely used models for large-scale data mining is the k-nearest neighbor (k-nn) algorithm. It can be used for classification, regression, density estimation, and information retrieval. To use k-nn, a practitioner must first choose k, usually selecting the k with the minimal loss estimated by cross-validation. In this work, we begin with an existing but little-studied method that...

Trip Pattern Mining Using Large Scale Geo-tagged Photos

Photo-sharing websites allows people to display their experiences on the Web through rich media data such as photos and videos. These photos contain spatial context in terms of latitude and longitude where the photo was taken. The geotagged photos disclose much information about people travel behavior and tourist density. As web-based and mobile-based technologies advance, geo-tagged photos are...

Mining Large-Scale Retail Data

Understanding customer buying patterns is of great interest in the retail industry. Applications include targeted advertising, optimized product placement, and cross-promotions. Association rules, expressed as A → B (if A then B) are a common and easily understandable ways to represent buying patterns. While the problem of mining such rules has received considerable attention over the past year...