Angular k-means for text mining
AssigneeIntel Corporation
InventorPiotr Tylenda
Life of this patent
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Abstract
An embodiment of a semiconductor package apparatus may include a substrate, and logic coupled to the substrate, wherein the logic is at least partly implemented in one or more of configurable logic and fixed-functionality hardware logic, the logic coupled to the substrate to determine an angular distance between a data object and a group of data objects, and assign the data object to the group of data objects based on the determined angular distance. In some embodiments, the logic may also be to determine one or more of an upper bound and a lower bound for the group of data objects based on triangle inequality. Other embodiments are disclosed and claimed.
Claims16
An electronic processing system, comprising:
- a processor;
- memory communicatively coupled to the processor;
- and
- logic communicatively coupled to the processor to:
- identify a dataset of N data objects,
- identify K centroids,
- determine an angular distance between a first data object of the data objects and a first centroid of the centroids,
- assign the first data object to the first centroid based on the determined angular distance,
- generate a N by K matrix of respective lower bounds, for each data object of the data objects and each centroid of the centroids, based on a triangle inequality, and
- generate an array of size N of respective upper bounds for each data object of the data objects based on the triangle inequality.
A semiconductor package apparatus, comprising:
- a substrate;
- and
- logic coupled to the substrate, wherein the logic is at least partly implemented in one or more of configurable logic or fixed-functionality logic hardware, the logic coupled to the substrate to:
- identify a dataset of N data objects,
- identify K centroids,
- determine an angular distance between a first data object of the data objects and a first centroid of the centroids,
- assign the first data object to the first centroid based on the determined angular distance,
- generate a N by K matrix of respective lower bounds, for each data object of the data objects and each centroid of the centroids, based on a triangle inequality, and
- generate an array of size N of respective upper bounds for each data object of the data objects based on the triangle inequality.
A method of grouping data objects, comprising:
- identifying a dataset of N data objects;
- identifying K centroids;
- determining an angular distance between a first data object of the data objects and a first centroid of the centroids;
- assigning the first data object to the first centroid based on the determined angular distance;
- generating a N by K matrix of respective lower bounds, for each data object of the data objects and each centroid of the centroids, based on a triangle inequality;
- and
- generating an array of size N of respective upper bounds for each data object of the data objects based on the triangle inequality.
At least one non-transitory computer readable medium, comprising a set of instructions, which when executed by a computing device, cause the computing device to:
- identify a dataset of N data objects;
- identify K centroids;
- determine an angular distance between a first data object of the data objects and first centroid of the centroids;
- assign the first data object to the first centroid based on the determined angular distance;
- generate a N by K matrix of respective lower bounds, for each data object of the data objects and each centroid of the centroids, based on a triangle inequality;
- and
- generate an array of size N of respective upper bounds for each data object of the data objects based on the triangle inequality.
Dependencies are inferred from the claim text.