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Full-Text Articles in Physical Sciences and Mathematics
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Graduate Theses and Dissertations
Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …
Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger
Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger
Computer Science and Computer Engineering Undergraduate Honors Theses
Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of …
Entity Based Sentiment Analysis For Textual Health Advice, Dae Lim Chung
Entity Based Sentiment Analysis For Textual Health Advice, Dae Lim Chung
Computer Science Senior Theses
This work explores entity based sentiment analysis for textual health advice through deep learning. We fine tuned a pretrained BERT model to analyze sentiments across five different predetermined categories which consist of food, medicine, disease, exercise, and vitality for three different sentiments: positive, negative, and neutral. Original set of annotated medical dataset from Dartmouth College’s Persist Lab was used to conduct the experiments. For the aim of tailoring the data for the purpose of entity based sentiment analysis, we explored data transformation techniques to generate optimum training examples. During the experiments, we were able to discover that the wide variety …
Caption And Image Based Next-Word Auto-Completion, Meet Patel
Caption And Image Based Next-Word Auto-Completion, Meet Patel
Master's Projects
With the increasing number of options or choices in terms of entities like products, movies, songs, etc. which are now available to users, they try to save time by looking for an application or system that provides automatic recommendations. Recommender systems are automated computing processes that leverage concepts of Machine Learning, Data Mining and Artificial Intelligence towards generating product recommendations based on a user’s preferences. These systems have given a significant boost to businesses across multiple segments as a result of reduced human intervention. One similar aspect of this is content writing. It would save users a lot of time …