M
Matthew England
Researcher at Coventry University
Publications - 137
Citations - 1800
Matthew England is an academic researcher from Coventry University. The author has contributed to research in topics: Cylindrical algebraic decomposition & Symbolic computation. The author has an hindex of 21, co-authored 125 publications receiving 1458 citations. Previous affiliations of Matthew England include University of Glasgow & Heriot-Watt University.
Papers
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Proceedings ArticleDOI
Arabic language sentiment analysis on health services
TL;DR: In this article, the authors introduce an Arabic language dataset, which is about opinions on health services and has been collected from Twitter, and they used several Machine Learning algorithms (Naive Bayes, Support Vector Machine and Logistic Regression) alongside Deep and Convolutional Neural Networks were utilized in their experiments of sentiment analysis on their health dataset.
Book ChapterDOI
A Combined CNN and LSTM Model for Arabic Sentiment Analysis
TL;DR: The benefits of integrating CNNs and LSTMs are investigated and improved accuracy for Arabic sentiment analysis on different datasets is obtained and it is sought to consider the morphological diversity of particular Arabic words by using different sentiment classification levels.
Book ChapterDOI
A Combined CNN and LSTM Model for Arabic Sentiment Analysis
TL;DR: In this paper, the authors investigated the benefits of integrating CNNs and LSTMs and reported improved accuracy for Arabic sentiment analysis on different datasets, considering the morphological diversity of particular Arabic words by using different sentiment classification levels.
Journal ArticleDOI
Truth table invariant cylindrical algebraic decomposition
TL;DR: An extended version of McCallum's theory of reduced projection operators is presented which can be applied to an arbitrary list of formulae, achieving savings if at least one has an equational constraint.
Book ChapterDOI
Applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition
Zongyan Huang,Matthew England,David Wilson,James H. Davenport,Lawrence C. Paulson,James P. Bridge +5 more
TL;DR: In this paper, a support vector machine (SVM) is used to select between heuristics for choosing a variable ordering in CAD, outperforming each of the separate heuristic.