1. Guided sampling for large graphs

   • Muhammad Irfan Yousuf
   • Suhyun Kim

   OriginalPaper 18 March 2020 Pages: 905 - 948

   

2. The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code

   • Yan Zhu
   • Shaghayegh Gharghabi
   • Eamonn Keogh

   OriginalPaper 31 March 2020 Pages: 949 - 979

   

3. Counting frequent patterns in large labeled graphs: a hypergraph-based approach

   • Jinghan Meng
   • Napath Pitaksirianan
   • Yi-Cheng Tu

   OriginalPaper 05 May 2020 Pages: 980 - 1021

   

4. Matrix profile goes MAD: variable-length motif and discord discovery in data series

   • Michele Linardi
   • Yan Zhu
   • Eamonn Keogh

   OriginalPaper 07 May 2020 Pages: 1022 - 1071

   

5. struc2gauss: Structural role preserving network embedding via Gaussian embedding

   • Yulong Pei
   • Xin Du
   • Mykola Pechenizkiy

   OriginalPaper Open access 12 May 2020 Pages: 1072 - 1103

   

6. An ultra-fast time series distance measure to allow data mining in more complex real-world deployments

   • Shaghayegh Gharghabi
   • Shima Imani
   • Eamonn Keogh

   OriginalPaper 30 May 2020 Pages: 1104 - 1135

   

7. TEAGS: time-aware text embedding approach to generate subgraphs

   • Saeid Hosseini
   • Saeed Najafipour
   • Xiaofang Zhou

   OriginalPaper 03 June 2020 Pages: 1136 - 1174

   

8. ABBA: adaptive Brownian bridge-based symbolic aggregation of time series

   • Steven Elsworth
   • Stefan Güttel

   OriginalPaper Open access 03 June 2020 Pages: 1175 - 1200

   

9. Efficient mining of the most significant patterns with permutation testing

   • Leonardo Pellegrina
   • Fabio Vandin

   OriginalPaper 09 June 2020 Pages: 1201 - 1234