2019
ACL
ACL 2019
Why Didn’t You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models
Abstract
AbstractTo address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments. These approaches extend previously proposed frameworks, including constraints and informed prior-based methods. Users should have a sense of control in HLTM systems, so we propose a control metric to measure whether refinement operations’ results match users’ expectations. Informed prior-based methods provide better control than constraints, but constraints yield higher quality topics.
❓
The Questioner
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning
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Keyword Pioneer
— user control
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Machine Learning, Natural Language Processing
Authors
Topics
Artificial Intelligence > Core AI > Human-AI Interaction
Artificial Intelligence > Core AI > Interpretability
Machine Learning > Core Methods > Clustering
Machine Learning > Learning Types > Active Learning
Natural Language Processing > Applications > Text Classification
Machine Learning > Core Methods > Topic Modeling
Machine Learning > Learning Types > Interactive Learning