Name
Abstract | ||
|---|---|---|
Knowledge-Based Question Answering (KBQA) is a novel method for Question Answering. To construct the semantic parser for a given question, it is vital to effectively encode the existing question for question classification. In this work, we propose a novel Multi-granularity fusion deep learning architecture that consists of sequence encoding, phrase vector recombination and feature extraction for ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CCIS53392.2021.9754664 | 2021 IEEE 7th International Conference on Cloud Computing and Intelligent Systems (CCIS) |
Keywords | DocType | ISBN |
Deep learning,Cloud computing,Computational modeling,Conferences,Semantics,Knowledge based systems,Computer architecture | Conference | 978-1-6654-4149-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yingpei Ma | 1 | 0 | 0.34 |
| Jing Wang | 2 | 28 | 23.94 |
| Yonghao Ren | 3 | 0 | 0.34 |
| Shuo Zhang | 4 | 0 | 0.34 |
| Runzhi Li | 5 | 6 | 1.17 |