Knowledge-Driven Event Embedding for Stock Prediction

By Xiao Ding, Ting-Wei Liu, Junwen Duan. 2016

126 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Philip S. Yu
2. Xi Zhang
3. Ziniu Hu
4. Bilal Abu-Salih
5. Yunjia Zhang
6. Senzhang Wang
7. Jiang Bian
8. Tie-Yan Liu

Citations in the corpus

• Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction (2017, background): “They further augmented their approach [6] by incorporating an outside knowledge graph into the learning process for event embeddings.”
• Improving stock market prediction via heterogeneous information fusion (2017, background): “Recently, the external information from knowledge graphs is incorporated into the learning process to generate event representations [6].”
• Domain-specific Knowledge Graphs: A survey (2020, background): “Authors of [145] depicted the relevance of using a knowledge-empowered model on event representation and stock prediction.”