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Graph-based Topic Extraction from Vector Embeddings of Text Documents: Application to a Corpus of News Articles
M. Tarik Altuncu, Sophia N. Yaliraki, Mauricio Barahona
Production of news content is growing at an astonishing rate. To help manage and monitor the sheer amount of text, there is an increasing need to develop efficient methods that can…
From Free Text to Clusters of Content in Health Records: An Unsupervised Graph Partitioning Approach
M. Tarik Altuncu, Erik Mayer, Sophia N. Yaliraki +1
Electronic Healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed…
Content-driven, unsupervised clustering of news articles through multiscale graph partitioning
M. Tarik Altuncu, Sophia N. Yaliraki, Mauricio Barahona
The explosion in the amount of news and journalistic content being generated across the globe, coupled with extended and instantaneous access to information through online media, m…
From Text to Topics in Healthcare Records: An Unsupervised Graph Partitioning Methodology
M. Tarik Altuncu, Erik Mayer, Sophia N. Yaliraki +1
Electronic Healthcare Records contain large volumes of unstructured data, including extensive free text. Yet this source of detailed information often remains under-used because of…