z-logo
open-access-imgOpen Access
ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback
Author(s) -
Yuheng Hu,
Ajita John,
Fei Wang,
Subbarao Kambhampati
Publication year - 2021
Publication title -
proceedings of the aaai conference on artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2374-3468
pISSN - 2159-5399
DOI - 10.1609/aaai.v26i1.8106
Subject(s) - crowds , computer science , event (particle physics) , joint (building) , segmentation , scale (ratio) , baseline (sea) , data science , artificial intelligence , topic model , machine learning , information retrieval , computer security , geography , political science , architectural engineering , physics , cartography , quantum mechanics , law , engineering

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom