GSSF: A Generative Sequence Similarity Function Based on a Seq2Seq Model for Clustering Online Handwritten Mathematical Answers

Quang Huy Ung, Cuong Tuan Nguyen, Hung Tuan Nguyen, Masaki Nakagawa. GSSF: A Generative Sequence Similarity Function Based on a Seq2Seq Model for Clustering Online Handwritten Mathematical Answers. In Josep Lladós 0001, Daniel Lopresti, Seiichi Uchida, editors, 16th International Conference on Document Analysis and Recognition, ICDAR 2021, Lausanne, Switzerland, September 5-10, 2021, Proceedings, Part II. Volume 12822 of Lecture Notes in Computer Science, pages 145-159, Springer, 2021. [doi]

@inproceedings{UngNNN21,
  title = {GSSF: A Generative Sequence Similarity Function Based on a Seq2Seq Model for Clustering Online Handwritten Mathematical Answers},
  author = {Quang Huy Ung and Cuong Tuan Nguyen and Hung Tuan Nguyen and Masaki Nakagawa},
  year = {2021},
  doi = {10.1007/978-3-030-86331-9_10},
  url = {https://doi.org/10.1007/978-3-030-86331-9_10},
  researchr = {https://researchr.org/publication/UngNNN21},
  cites = {0},
  citedby = {0},
  pages = {145-159},
  booktitle = {16th International Conference on Document Analysis and Recognition, ICDAR 2021, Lausanne, Switzerland, September 5-10, 2021, Proceedings, Part II},
  editor = {Josep Lladós 0001 and Daniel Lopresti and Seiichi Uchida},
  volume = {12822},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-86331-9},
}