[HTML][HTML] Achieving approximate global optimization of truth inference for crowdsourcing microtasks
Microtask crowdsourcing is a form of crowdsourcing in which work is decomposed into a set
of small, self-contained tasks, which each can typically be completed in a matter of minutes …
of small, self-contained tasks, which each can typically be completed in a matter of minutes …
Learning from biased crowdsourced labeling with deep clustering
With the rapid development of crowdsourcing learning, amount of labels can be obtained
from crowd workers fast and cheaply. However, crowdsourcing learning also faces …
from crowd workers fast and cheaply. However, crowdsourcing learning also faces …
Learning from Crowds Using Graph Neural Networks with Attention Mechanism
Crowdsourcing has been playing an essential role in machine learning since it can obtain a
large number of labels in an economical and fast manner for training increasingly complex …
large number of labels in an economical and fast manner for training increasingly complex …
A computational model implementing subjectivity with the'Room Theory'. The case of detecting Emotion from Text
C Lipizzi, D Borrelli, FO Capela - arXiv preprint arXiv:2005.06059, 2020 - arxiv.org
This work introduces a new method to consider subjectivity and general context dependency
in text analysis and uses as example the detection of emotions conveyed in text. The …
in text analysis and uses as example the detection of emotions conveyed in text. The …
Recommending recommendations to support the Defense Acquisition Workforce
C Lipizzi, H Behrooz, M Dressman, AG Vishwakumar… - 2022 - dair.nps.edu
This paper presentings the preliminary results of a research study to support the Defense
Acquisition Workforce with a Natural Language Processing (NLP)/Machine Learning (ML) …
Acquisition Workforce with a Natural Language Processing (NLP)/Machine Learning (ML) …