Time series data poses a significant variation to the traditional segmentation techniques of data mining because the observation is derived from multiple instances of the same und...
In this paper, a pattern-based stock data mining approach which transforms the numeric stock data to symbolic sequences, carries out sequential and non-sequential association analy...
Abstract-- Mining textual documents and time series concurrently, such as predicting the movements of stock prices based on the contents of the news stories, is an emerging topic i...
Gabriel Pui Cheong Fung, Jeffrey Xu Yu, Hongjun Lu
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...