Project Details
Description
The information workload can be reduced when machine reading can provide literature summaries and overviews of new ideas. Professor Yi-Ke Guo, at Imperial College London, is using Elsevier data to understand the interaction between world knowledge and language via deep learning and natural language processing techniques. To accomplish this, a large set of documents is fed to a framework based on deep neural networks, which is then trained to make inferences about knowledge and create new documents based on vocabularies and ontologies provided by Professor Guo's Team.
| Status | Finished |
|---|---|
| Effective start/end date | 10/1/15 → 03/1/20 |
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Deep sequence learning with auxiliary information for traffic prediction
Gao, Y., Feb 1 2019.Research output: Contribution to conference › Paper › peer-review
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Integrating Semantic Knowledge to Tackle Zero-shot Text Classification
Gao, Y., Zhang, J. & Lertvittayakumjorn, P., May 1 2019, In: ARXIV.Research output: Contribution to journal › Article › peer-review
84 Link opens in a new tab Scopus citations -
Dest-ResNet: A Deep Spatiotemporal Residual Network for Hotspot Traffic Speed Prediction
Zhang, J. & Gao, Y., 2018, In: Journal of the ACM.Research output: Contribution to journal › Article › peer-review
30 Link opens in a new tab Scopus citations
Press/Media
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The new faces of data science
Augenstein, I., Hobby, M., Gao, Y., Gregory, K., Siebert, M., Haak, W., Groth, P., Hoekstra, R. & Tsatsaronis, G.
10/1/17
1 Media contribution
Press/Media