METHOD FOR EXTRACTING A COMPACT REPRESENTATION OF THE TOPICAL CONTENT OF AN ELECTRONIC TEXT

Patent №

US 7,587,381

Granted

2009-09-08

Filed 2003

Owner

THINK TANK 23 LLC

+4 more

Lab

AI components

4

ml · nlp · vision · kr

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

10350869

An electronic document is parsed to remove irrelevant text and to identify the significant elements of the retained text. The elements are assigned scores representing their significance to the topical content of the document. A matrix of element-pairs is constructed such that the matrix nodes represent the result of one or more functions of the scores and other attributes of the paired elements. The resulting matrix is a compact representation of topical content that affords great precision in information retrieval applications that depend on measurements of the relatedness of topical content.

Machine learningNatural languageVisionKnowledge representationG06F 16/313Y10S 707/99931Y10S 707/99932Y10S 707/99933

AI classification

Natural language1.00
Machine learning1.00
Vision1.00
Knowledge representation0.81
AI hardware0.15
Planning0.10
Speech0.00
Evolutionary computation0.00

Ownership

THINK TANK 23 LLC

assignment · 202810027

SPHERE SOURCE, INC.

assignment · 202810063

SURPHACE ACQUISITION, INC.

assignment · 257430896

OUTBRAIN, INC.

assignment · 350170809

SURPHACE INC.

namechg · 350900228

Assignors

NIEKER, STEVEN, REMY, MARTIN

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

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