Special Issue on Application-Driven Knowledge Acquisition

Articles (8 in this collection)

1. Editorial for application-driven knowledge acquisition

   Authors

   • Xue Li
   • Sen Wang
   • Bohan Li

   • Content type: EditorialNotes
   • Published: 25 June 2020

   • Pages: 2649 - 2651

2. Fine-grained emotion classification of Chinese microblogs based on graph convolution networks

   Authors (first, second and last of 5)

   • Yuni Lai
   • Linfeng Zhang
   • Guoren Wang

   • Content type: OriginalPaper
   • Published: 17 June 2020

   • Pages: 2771 - 2787

   

3. Embedding geographic information for anomalous trajectory detection

   Authors (first, second and last of 6)

   • Ding Xiao
   • Li Song
   • Chuan Shi

   • Content type: OriginalPaper
   • Published: 17 April 2020

   • Pages: 2789 - 2809

   

4. Multi-view network embedding with node similarity ensemble

   Authors (first, second and last of 7)

   • Weiwei Yuan
   • Kangya He
   • Mohammed Al-Dhelaan

   • Content type: OriginalPaper
   • Published: 12 March 2020

   • Pages: 2699 - 2714

   

5. Deep learning for heterogeneous medical data analysis

   Authors (first, second and last of 5)

   • Lin Yue
   • Dongyuan Tian
   • Minghao Yin

   • Content type: OriginalPaper
   • Published: 07 March 2020

   • Pages: 2715 - 2737

   

6. Graph augmented triplet architecture for fine-grained patient similarity

   Authors (first, second and last of 4)

   • Yanda Wang
   • Weitong Chen
   • Robert Boots

   • Content type: OriginalPaper
   • Published: 29 February 2020

   • Pages: 2739 - 2752

   

7. AMRNN: attended multi-task recurrent neural networks for dynamic illness severity prediction

   Authors (first, second and last of 4)

   • Weitong Chen
   • Guodong Long
   • Quan Z. Sheng

   • Content type: OriginalPaper
   • Published: 21 September 2019

   • Pages: 2753 - 2770

   

8. Knowledge graph construction from multiple online encyclopedias

   Authors (first, second and last of 8)

   • Tianxing Wu
   • Haofen Wang
   • Chaomin Shi

   • Content type: OriginalPaper
   • Published: 14 September 2019

   • Pages: 2671 - 2698