Large-Scale Price Interval Prediction at OTA Sites

Large Scale Disease Prediction

The objective of this thesis is to present the foundation of an automated large-scale disease prediction system. Unlike previous work that has typically focused on a small self-contained dataset, we explore the possibility of combining a large amount of heterogenous data to perform gene selection and phenotype classification. First, a subset of publicly available microarray datasets was downloa...

Large-Scale Price Optimization via Network Flow

This paper deals with price optimization, which is to find the best pricing strategy that maximizes revenue or profit, on the basis of demand forecasting models. Though recent advances in regression technologies have made it possible to reveal price-demand relationship of a large number of products, most existing price optimization methods, such as mixed integer programming formulation, cannot ...

Large Scale Reasoning Using Allen's Interval Algebra

This paper proposes and evaluates a distributed, parallel approach for reasoning over large scale datasets using Allen’s Interval Algebra (IA). We have developed and implemented algorithms that reason over IA networks using the Spark distributed processing framework. Experiments have been conducted by deploying the algorithms on computer clusters using synthetic datasets with various characteri...

Prediction and large scale data

Crude Oil Price Prediction Based On Multi-scale Decomposition

A synergetic model (DWT-LSSVM) is presented in this paper. First of all, the raw data is decomposed into approximate coefficients and the detail coefficients at different scales by discrete wavelet transforms (DWT). These coefficients obtained by previous phase are then used for prediction independently using least squares support vector machines (LSSVM). Finally, these predicted coefficients a...