IMPORTANCE RANKING FOR A HIERARCHICAL COLLECTION OF OBJECTS

Patent №

US 7,809,736

Granted

2010-10-05

Filed 2007

Owner

BROWN UNIVERSITY

Lab

AI components

4

ml · vision · kr · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11919262

A system and method of obtaining an importance ranking for a hierarchical collection of objects. The hierarchical collection of objects is represented as a tree containing a plurality of nodes, and each node to be ranked is represented as a respective leaf node of the tree. To obtain the ranking of the respective leaf nodes, the system and method locally ranks nodes contained in one or more sub-trees of the tree, in which each sub-tree has a depth equal to one. Next, the local rankings are effectively propagated up the tree, and the local rankings are aggregated at each level of the hierarchy, until a final importance ranking for the leaf nodes is obtained.

AI classification

Knowledge representation1.00
Machine learning0.99
AI hardware0.97
Vision0.87
Evolutionary computation0.01
Natural language0.00
Speech0.00
Planning0.00

Ownership

BROWN UNIVERSITY

assignment · 200760006

Assignors

GREENWALD, AMY, WICKS, JOHN R.

On an employer assignment, the assignors are typically the inventors.

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