The Classic Security Application in M2M: the Authentication Scheme of Mobile Payment. - Liang Hu 001; Ling Chi; Hongtu Li; Wei Yuan; Yuyu Sun; Jianfeng Chu (KSII Trans. Internet Inf. Syst., 2012)

Analysis and Improvement of a Robust User Authentication Framework for Ubiquitous Sensor Networks. - Ling Chi; Liang Hu 001; Hongtu Li; Jianfeng Chu (Int. J. Distributed Sens. Networks, 2014)

The maximum matching degree sifting algorithm for steganography pretreatment applied to IoT. - Huifeng Li; Liang Hu 001; Jianfeng Chu; Ling Chi; Hongtu Li (Multim. Tools Appl., 2018)

An Unsupervised Approach for Keyphrase Extraction Using Within-Collection Resources. - Tengfei Li 004; Liang Hu 001; Jianfeng Chu; Hongtu Li; Ling Chi (IEEE Access, 2019)

A Reversible Data Hiding Algorithm Based on Prediction Error With Large Amounts of Data Hiding in Spatial Domain. - Shuai Li; Liang Hu 001; Chengyu Sun; Ling Chi; Tuohang Li; Hongtu Li (IEEE Access, 2020)

A Review of Unsupervised Keyphrase Extraction Methods Using Within-Collection Resources. - Chengyu Sun; Liang Hu 001; Shuai Li; Tuohang Li; Hongtu Li; Ling Chi (Symmetry, 2020)

ISKE: An unsupervised automatic keyphrase extraction approach using the iterated sentences based on graph method. - Ling Chi; Liang Hu 001 (Knowl. Based Syst., 2021)

TripleRank: An unsupervised keyphrase extraction algorithm. - Tuohang Li; Liang Hu 001; Hongtu Li; Chengyu Sun; Shuai Li; Ling Chi (Knowl. Based Syst., 2021)

Comparative assessment of PEE methods and new performance measurement for RDH. - Shuai Li; Liang Hu 001; Chengyu Sun; Ling Chi; Hongtu Li (Multim. Tools Appl., 2021)

Towards unsupervised keyphrase extraction via an autoregressive approach. - Tuohang Li; Liang Hu 001; Hongtu Li; Chengyu Sun; Shuai Li; Ling Chi (Knowl. Based Syst., 2023)

IKAR: An Interdisciplinary Knowledge-Based Automatic Retrieval Method from Chinese Electronic Medical Record. - Yueming Zhao; Liang Hu; Ling Chi (Inf., 2023)

Predicting relations between SOAP note sections: The value of incorporating a clinical information model. - Vimig Socrates; Aidan Gilson; Kevin Lopez; Ling Chi; Richard Andrew Taylor; David Chartash (J. Biomed. Informatics, 2023)

HAT-GAE: Self-supervised graph autoencoders with hierarchical adaptive masking and trainable corruption. - Chengyu Sun; Liang Hu 001; Hongtu Li; Shuai Li; Tuohang Li; Ling Chi (Knowl. Based Syst., 2023)