FULL-TEXT RELEVANCY RANKING

Patent №

US 8,095,529

Granted

2012-01-10

Filed 2005

Owner

AMERICA ONLINE, INC.

+1 more

Lab

AI components

3

ml · nlp · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11029892

A method and system for ranking relevancy of metadata associated with media on a computer network, such as multimedia and streaming media, include categorizing the metadata into sets of metadata. The categories are broad categories relating to areas such as who, what, when, and where, such as artist, media type, and creation date, creation location. Weights are assigned to each set of metadata. Weights are related to technical information such as bit rate, duration, sampling rate, frequency of occurrence of a specific term, etc. A score is calculated for ranking the relevancy of each set of metadata. The score is calculated in accordance with the assigned weight and category. This score is available for search systems (e.g., search engines) and/or users to determine the relative ranking of search results.

Machine learningNatural languageAI hardwareG06F 16/27G06F 16/41G06F 16/4387G06F 16/48G06F 16/907G06F 16/908G06F 16/951G06F 16/9535+12 more

AI classification

Natural language1.00
Machine learning0.98
AI hardware0.72
Knowledge representation0.19
Speech0.16
Vision0.04
Planning0.02
Evolutionary computation0.00

Ownership

AMERICA ONLINE, INC.

assignment · 202230361

THOMSON LICENSING S.A.

assignment · 244210862

Assignors

DIAMOND, THEODORE GEORGE, HENDRICK, DANIEL ALLEN, REHM, ERIC CARL, RIESLAND, MELISSA ANNE

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

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