Invention Application
- Patent Title: DYNAMIC CLUSTERING OF SPARSE DATA UTILIZING HASH PARTITIONS
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Application No.: US16852110Application Date: 2020-04-17
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Publication No.: US20210326361A1Publication Date: 2021-10-21
- Inventor: Fan Du , Yeuk-Yin Chan , Eunyee Koh , Ryan Rossi , Margarita Savova , Charles Menguy , Anup Rao
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Main IPC: G06F16/28
- IPC: G06F16/28 ; G06F16/22

Abstract:
The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing hash partitions to determine local densities and distances among users (or among other represented data points) for clustering sparse data into segments. For instance, the disclosed systems can generate hash signatures for users in a sparse dataset and can map users to hash partitions based on the hash signatures. The disclosed systems can further determine local densities and separation distances for particular users (or other represented data points) within the hash partitions. Upon determining local densities and separation distances for datapoints from the dataset, the disclosed systems can select a segment (or cluster of data points) grouped according to a hierarchy of a clustering algorithm, such as a density-peaks-clustering algorithm.
Public/Granted literature
- US11328002B2 Dynamic clustering of sparse data utilizing hash partitions Public/Granted day:2022-05-10
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