Neural net models for open-domain discourse coherence
J Li, D Jurafsky - arXiv preprint arXiv:1606.01545, 2016 - arxiv.org
Discourse coherence is strongly associated with text quality, making it important to natural
language generation and understanding. Yet existing models of coherence focus on …
language generation and understanding. Yet existing models of coherence focus on …
Zero-shot multi-label topic inference with sentence encoders and llms
In this paper, we conducted a comprehensive study with the latest Sentence Encoders and
Large Language Models (LLMs) on the challenging task of “definition-wild zero-shot topic …
Large Language Models (LLMs) on the challenging task of “definition-wild zero-shot topic …
[PDF][PDF] Topic segmentation with a structured topic model
We present a new hierarchical Bayesian model for unsupervised topic segmentation. This
new model integrates a point-wise boundary sampling algorithm used in Bayesian …
new model integrates a point-wise boundary sampling algorithm used in Bayesian …
Ad-hoc monitoring of covid-19 global research trends for well-informed policy making
The COVID-19 pandemic has affected millions of people worldwide with severe health,
economic, social, and political implications. Healthcare Policy Makers (HPMs) and medical …
economic, social, and political implications. Healthcare Policy Makers (HPMs) and medical …
[HTML][HTML] Key concerns and drivers of low-cost air quality sensor use
PN deSouza - Sustainability, 2022 - mdpi.com
Low-cost sensors are revolutionizing air pollution monitoring by providing real-time, highly
localized air quality information. The relatively low-cost nature of these devices has made …
localized air quality information. The relatively low-cost nature of these devices has made …
Hidden topic–emotion transition model for multi-level social emotion detection
With the fast development of online social platforms, social emotion detection, focusing on
predicting readers' emotions evoked by news articles, has been intensively investigated …
predicting readers' emotions evoked by news articles, has been intensively investigated …
Topic extraction from microblog posts using conversation structures
Conventional topic models are ineffective for topic extraction from microblog messages
since the lack of structure and context among the posts renders poor message-level word co …
since the lack of structure and context among the posts renders poor message-level word co …
Hidden topic sentiment model
Various topic models have been developed for sentiment analysis tasks. But the simple topic-
sentiment mixture assumption prohibits them from finding fine-grained dependency between …
sentiment mixture assumption prohibits them from finding fine-grained dependency between …
[PDF][PDF] Mixed membership Markov models for unsupervised conversation modeling
M Paul - Proceedings of the 2012 joint conference on empirical …, 2012 - aclanthology.org
Recent work has explored the use of hidden Markov models for unsupervised discourse and
conversation modeling, where each segment or block of text such as a message in a …
conversation modeling, where each segment or block of text such as a message in a …
Time series analysis of nursing notes for mortality prediction via a state transition topic model
Accurate mortality prediction is an important task in intensive care units in order to channel
prompt care to patients in the most critical condition and to reduce nurses' alarm fatigue …
prompt care to patients in the most critical condition and to reduce nurses' alarm fatigue …