Indexing of large scale patient set
AssigneeInternational Business Machines Corporation
InventorsFei Wang, Jun Wang
Life of this patent
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Abstract
Systems and methods for indexing data include formulating an objective function to index a dataset, a portion of the dataset including supervision information. A data property component of the objective function is determined, which utilizes a property of the dataset to group data of the dataset. A supervised component of the objective function is determined, which utilizes the supervision information to group data of the dataset. The objective function is optimized using a processor based upon the data property component and the supervised component to partition a node into a plurality of child nodes.
Claims8
A non-transitory computer readable storage medium comprising a computer readable program for indexing data, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:
- formulating an objective function to index a dataset, a portion of the dataset including supervision information;
- determining a data property component and a supervised component for grouping data of the dataset, the determining the data property component including maximizing a variance of the dataset by applying a principal component analysis (PCA) and maximum variance unfolding (MVU), the MVU comprising forming an inner product of a data matrix and a learned partition hyperplane and maximizing overall pairwise distances in a projected space to reduce computational costs during the indexing, and the PCA comprising determining an eigenvector from a data covariance matrix with a largest corresponding eigenvector;
- and
- optimizing, using a processor, the objective function based upon the data property component and the supervised component to partition a node into a plurality of child nodes.
A system for indexing data, comprising:
- a processor operatively coupled to a memory, the processor being configured to:
- formulate an objective function to index a dataset stored on a computer readable storage medium, a portion of the dataset including supervision information;
- determine a data property component and a supervision module configured to determine a supervised component of the objective function for grouping data of the dataset, the data property component being determined by maximizing a variance of the dataset by applying a principal component analysis (PCA) and maximum variance unfolding (MVU), MVU comprising forming an inner product of a data matrix and a learned partition hyperplane and maximizing overall pairwise distances in a projected space to reduce computational costs during the indexing, and the PCA comprising determining an eigenvector from a data covariance matrix with a largest corresponding eigenvector;
- and
- optimize the objective function based upon the data property component and the supervised component to partition a node into a plurality of child nodes.
Dependencies are inferred from the claim text.