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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences

Technological University Dublin

2021

Machine learning

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Monitoring Quality Of Life Indicators At Home From Sparse And Low-Cost Sensor Data., Dympna O'Sullivan, Rilwan Basaru, Simone Stumpf, Neil Maiden Jun 2021

Monitoring Quality Of Life Indicators At Home From Sparse And Low-Cost Sensor Data., Dympna O'Sullivan, Rilwan Basaru, Simone Stumpf, Neil Maiden

Conference papers

Supporting older people, many of whom live with chronic conditions or cognitive and physical impairments, to live independently at home is of increasing importance due to ageing demographics. To aid independent living at home, much effort is being directed at reliably detecting activities from sensor data to monitor people’s quality of life or to enhance self-management of their own health. Current efforts typically leverage smart homes which have large numbers of sensors installed to overcome challenges in the accurate detection of activities. In this work, we report on the results of machine learning models based on data collected with a …


Interactive Learning Approach For Arabic Target-Based Sentiment Analysis, Husamelddin Balla, Marisa Llorens, Sarah Jane Delany Jan 2021

Interactive Learning Approach For Arabic Target-Based Sentiment Analysis, Husamelddin Balla, Marisa Llorens, Sarah Jane Delany

Conference papers

Recently, the majority of sentiment analysis researchers focus on target-based sentiment analysis because it delivers in-depth analysis with more accurate results as compared to traditional sentiment analysis. In this paper, we propose an interactive learning approach to tackle a target-based sentiment analysis task for the Arabic language. The proposed IALSTM model uses an interactive attentionbased mechanism to force the model to focus on different parts (targets) of a sentence. We investigate the ability to use targets, right and left contexts, and model them separately to learn their own representations via interactive modeling. We evaluated our model on two different datasets: …