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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Unsupervised Structural Graph Node Representation Learning, Mikel Joaristi
Unsupervised Structural Graph Node Representation Learning, Mikel Joaristi
Boise State University Theses and Dissertations
Unsupervised Graph Representation Learning methods learn a numerical representation of the nodes in a graph. The generated representations encode meaningful information about the nodes' properties, making them a powerful tool for tasks in many areas of study, such as social sciences, biology or communication networks. These methods are particularly interesting because they facilitate the direct use of standard Machine Learning models on graphs. Graph representation learning methods can be divided into two main categories depending on the information they encode, methods preserving the nodes connectivity information, and methods preserving nodes' structural information. Connectivity-based methods focus on encoding relationships between nodes, …
Improving Spellchecking For Children: Correction And Design, Brody Downs
Improving Spellchecking For Children: Correction And Design, Brody Downs
Boise State University Theses and Dissertations
Children commonly use software applications such as search engines and word processors in the classroom environment. However, a major barrier to using these programs successfully is the ability of children to type and spell effectively. While many programs make use of spellcheckers to provide spelling corrections to their users, they are designed for more traditional users (i.e., adults) and have proven inadequate for children. The aims of this work is twofold: first, to address the types of spelling errors children make by researching, developing, and evaluating algorithms to generate and rank candidate spelling suggestions; and second, to evaluate the impact …