M
Margaret Mitchell
Researcher at Google
Publications - 109
Citations - 18187
Margaret Mitchell is an academic researcher from Google. The author has contributed to research in topics: Computer science & Context (language use). The author has an hindex of 42, co-authored 94 publications receiving 13094 citations. Previous affiliations of Margaret Mitchell include University of Aberdeen & Johns Hopkins University.
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Proceedings Article
Two Approaches for Generating Size Modifiers
TL;DR: This paper isolates a set of features that may be used in a hand-coded algorithm or a machine learning approach to generate one of six basic size types, and finds a statistically significant difference between the precision and recall of the two systems.
Proceedings ArticleDOI
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned
TL;DR: This tutorial aims to present an overview of algorithmic bias / discrimination issues observed over the last few years and the lessons learned, key regulations and laws, and evolution of techniques for achieving fairness in machine learning systems.
Proceedings Article
Microsummarization of online reviews: an experimental study
Rebecca Mason,Benjamin Gaska,Benjamin Van Durme,Pallavi Choudhury,Ted Hart,Bill Dolan,Kristina Toutanova,Margaret Mitchell +7 more
TL;DR: The task of microsummarization is introduced, which combines sentiment analysis, summarization, and entity recognition in order to surface key content to users and finds it can reliably extract relevant entities and the sentiment targeted towards them using crowd-sourced labels as supervision.
Journal ArticleDOI
Guest Editorial: Image and Language Understanding
TL;DR: This special issue of IJCV is pleased to present: some of the latest work in a long line of research into problems at the intersection of computer vision and natural language processing on combined image and language understanding.
Journal Article
Overview of the TAC2013 Knowledge Base Population Evaluation: English Sentiment Slot Filling.
TL;DR: This document provides an overview of the Text Analysis Conference 2013 Knowledge Base Population Sentiment Slot Filling track, and focused on identifying the polarity of sentiment as well as sentiment holders and sentiment targets.