OPTIMIZING SEARCH TREES BY INCREASING FAILURE SIZE PARAMETER

Patent №

US 7,917,486

Granted

2011-03-29

Filed 2007

Owner

NETLOGIC MICROSYSTEMS, INC.

Lab

AI components

2

nlp · kr

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11689429

A search tree embodying a plurality of signatures to be compared with an input string of characters and including a number of branches of sequential states originating at a root node, wherein each state comprises a state entry including a failure transition and one or more success transitions, is optimized by selecting a failure size parameter indicating a minimum number of characters to be traversed on the failure transitions and selectively modifying the search tree to create a modified search tree for which all failure transitions to non-root states are characterized by the selected failure size parameter.

Natural languageKnowledge representationG06F 16/90344H04L 63/1416Y10S 707/99932Y10S 707/99936Y10S 707/99942

AI classification

Natural language0.62
Knowledge representation0.51
Planning0.10
AI hardware0.05
Evolutionary computation0.02
Vision0.01
Speech0.00
Machine learning0.00

Ownership

NETLOGIC MICROSYSTEMS, INC.

assignment · 192770824

Assignors

GUPTA, PANKAJ, VANKATACHARY, SRINIVASAN

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

From the same owner

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