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Title: Technologies for node-degree based clustering of data sets

Abstract

Technologies for node-degree based clustering include a computing device to construct a graph that includes multiple vertices corresponding to the data points of a data set. The computing device inserts an edge between each pair of vertices that has a corresponding similarity metric that meets a predetermined threshold similarity metric. The computing device determines a node degree for each vertex in the graph and initializes a cutoff node degree as the lowest node degree of the vertices. The computing device selects a test subset of the graph that includes vertices having a node degree less than or equal to the cutoff node degree. The computing device determines whether the test subset covers the graph and if not increases the cutoff node degree. If the test subset covers the graph, the data points corresponding to the vertices of the test subset are the representative cluster. Other embodiments are described and claimed.

Inventors:
;
Issue Date:
Research Org.:
Intel Corp., Santa Clara, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1600208
Patent Number(s):
10452717
Application Number:
15/272,976
Assignee:
Intel Corporation (Santa Clara, CA)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
DOE Contract Number:  
B608115-00-0-0000-0116
Resource Type:
Patent
Resource Relation:
Patent File Date: 09/22/2016
Country of Publication:
United States
Language:
English

Citation Formats

Sitik, Ahmet Can, and More, Ankit. Technologies for node-degree based clustering of data sets. United States: N. p., 2019. Web.
Sitik, Ahmet Can, & More, Ankit. Technologies for node-degree based clustering of data sets. United States.
Sitik, Ahmet Can, and More, Ankit. Tue . "Technologies for node-degree based clustering of data sets". United States. https://www.osti.gov/servlets/purl/1600208.
@article{osti_1600208,
title = {Technologies for node-degree based clustering of data sets},
author = {Sitik, Ahmet Can and More, Ankit},
abstractNote = {Technologies for node-degree based clustering include a computing device to construct a graph that includes multiple vertices corresponding to the data points of a data set. The computing device inserts an edge between each pair of vertices that has a corresponding similarity metric that meets a predetermined threshold similarity metric. The computing device determines a node degree for each vertex in the graph and initializes a cutoff node degree as the lowest node degree of the vertices. The computing device selects a test subset of the graph that includes vertices having a node degree less than or equal to the cutoff node degree. The computing device determines whether the test subset covers the graph and if not increases the cutoff node degree. If the test subset covers the graph, the data points corresponding to the vertices of the test subset are the representative cluster. Other embodiments are described and claimed.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {10}
}

Works referenced in this record:

Hierarchical Cluster Determination Based on Subgraph Density
patent-application, February 2014


Systems and Methods for Cluster Augmentation of Search Results
patent-application, March 2012


Systems and Methods for File Clustering, Multi-Drive Forensic Analysis and Data Protection
patent-application, May 2016


Method for modelling similarity function using neural network
patent, October 1995


Graph Processing Using a Mutable Multilevel Graph Representation
patent-application, March 2016