PREDICTING THE LOCATIONS OF UNREST USING SOCIAL MEDIA
暂无分享,去创建一个
[1] Andrew McCallum,et al. Maximum Entropy Markov Models for Information Extraction and Segmentation , 2000, ICML.
[2] James Hammerton,et al. Named Entity Recognition with Long Short-Term Memory , 2003, CoNLL.
[3] Chenliang Li,et al. A Survey on Deep Learning for Named Entity Recognition , 2018, IEEE Transactions on Knowledge and Data Engineering.
[4] Thomas Zeitzoff,et al. How Social Media Is Changing Conflict , 2017 .
[5] Francis L. F. Lee,et al. Affordances, movement dynamics, and a centralized digital communication platform in a networked movement , 2021, Information, Communication & Society.
[6] S. Eddy. Hidden Markov models. , 1996, Current opinion in structural biology.
[7] Yueran Zu,et al. An Encoding Strategy Based Word-Character LSTM for Chinese NER , 2019, NAACL.
[8] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[9] Wei Xu,et al. Bidirectional LSTM-CRF Models for Sequence Tagging , 2015, ArXiv.
[10] Yue Zhang,et al. Chinese NER Using Lattice LSTM , 2018, ACL.
[11] Guoxin Wang,et al. CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition , 2019, NAACL.
[12] Tobun Dorbin Ng,et al. Analyzing and Visualizing Web Opinion Development and Social Interactions With Density-Based Clustering , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[13] M. Purbrick. A REPORT OF THE 2019 HONG KONG PROTESTS , 2019, Asian Affairs.
[14] A. Breuer. The Role of Social Media in Mobilizing Political Protest: Evidence from the Tunisian Revolution , 2012 .
[15] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..