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Full-Text Articles in Physical Sciences and Mathematics
Probabilistic Latent Document Network Embedding, Tuan M. V. Le, Hady W. Lauw
Probabilistic Latent Document Network Embedding, Tuan M. V. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
A document network refers to a data type that can be represented as a graph of vertices, where each vertex is associated with a text document. Examples of such a data type include hyperlinked Web pages, academic publications with citations, and user profiles in social networks. Such data have very high-dimensional representations, in terms of text as well as network connectivity. In this paper, we study the problem of embedding, or finding a low-dimensional representation of a document network that "preserves" the data as much as possible. These embedded representations are useful for various applications driven by dimensionality reduction, such …
Urban Planning Process: Can Technology Enhance Participatory Communication?, Rojin Vishkaie, Richard Levy, Anthony Tang
Urban Planning Process: Can Technology Enhance Participatory Communication?, Rojin Vishkaie, Richard Levy, Anthony Tang
Research Collection School Of Computing and Information Systems
Oftentimes, within the urban planning process, urban planners and GIS experts must work together using desktop Computer-Aided Design (CAD) and Geographic Information System (GIS). However, participatory communication and visualization which are important in the urban planning process, are not a central focus in the design of current computer-aided planning technologies. This study tends to provide an understanding of technological challenges and complexities urban planners and GIS experts encounter while engaging in a participatory environment during the urban planning process. This study also explores the perceptions of urban planners and GIS experts about the potential impact and usefulness of interactive surfaces …
Manifold Learning For Jointly Modeling Topic And Visualization, Tuan Minh Van Le, Hady W. Lauw
Manifold Learning For Jointly Modeling Topic And Visualization, Tuan Minh Van Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Classical approaches to visualization directly reduce a document's high-dimensional representation into visualizable two or three dimensions, using techniques such as multidimensional scaling. More recent approaches consider an intermediate representation in topic space, between word space and visualization space, which preserves the semantics by topic modeling. We call the latter semantic visualization problem, as it seeks to jointly model topic and visualization. While previous approaches aim to preserve the global consistency, they do not consider the local consistency in terms of the intrinsic geometric structure of the document manifold. We therefore propose an unsupervised probabilistic model, called Semafore, which aims to …