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- W2897878977 abstract "Spherical k-means is a fast and effective method for clustering text documents in their directional representation over a unit hypersphere. Current needs of text clustering are related to clustering of streams. Due to memory restrictions, fast and effective methods are required that incur less space complexity. Few research works exist that have adapted spherical k-means to streaming text data, but recorded performance is not satisfactory for novelty detection imbalanced cluster structure. This paper presents streaming spherical k-means with associated facility location costs. Arriving documents are detected as new topic or join an existing depending on these costs." @default.
- W2897878977 created "2018-10-26" @default.
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- W2897878977 date "2018-03-01" @default.
- W2897878977 modified "2023-09-23" @default.
- W2897878977 title "Clustering of Text Streams via Facility Location and Spherical K-means" @default.
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- W2897878977 doi "https://doi.org/10.1109/iceca.2018.8474757" @default.
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