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In this project, we use skip-gram model to embed Wikipedia Concepts and Entities. The English version of Wikipedia contains more than five million pages, which suggest its capability to cover many …
Document clustering is an efficient way to get insight into large text collections. Due to the personalized nature of document clustering, even the best fully automatic algorithms cannot create clu…
KMeans is a document clustering algorithms. It is usually initialized randomly that can drastically impact the final algorithm performance. In this project, we introduce a novel deterministic seedi…
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