ITERATIVE SAMPLING BASED DATASET CLUSTERING

In some examples, iterative sampling based dataset clustering may include sampling a dataset that includes a plurality of items to identify a specified number of sampled items. The sampled items may be clustered to generate a plurality of clusters. Un-sampled items may be assigned from the plurality...

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Bibliographic Details
Main Authors PHILLIPS, Jaclyn Ruth Elizabeth, LI, Chao, SARAF, Ankit, HUANG, Jiayuan, WONG, Justin Carl, YUAN, Changhong, ABDELREHEEM, Eslam K, WANG, Yuantao, WATANABE, Tsuyoshi, ZHAO, Nan, WANG, Shean, MA, Yunjing, GUO, Xiaoying, CHEN, Weizhu
Format Patent
LanguageEnglish
Published 22.04.2021
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:In some examples, iterative sampling based dataset clustering may include sampling a dataset that includes a plurality of items to identify a specified number of sampled items. The sampled items may be clustered to generate a plurality of clusters. Un-sampled items may be assigned from the plurality of items to the clusters. Remaining un-sampled items that are not assigned to the clusters may be identified. A ratio associated with the remaining un-sampled items and the plurality of items may be compared to a specified threshold. Based on a determination that the ratio is greater than the specified threshold, an indication of completion of clustering of the plurality of items may be generated.
Bibliography:Application Number: US201916659017