IP Library › Granted Patent US 11,636,378
Granted Patent B2
US 11,636,378 · App. 16/113,861 · Granted Apr 25, 2023

Information processing apparatus, information processing method, and information processing system

Inventor: Naoki Matsuki (Tokyo, JP)
Assignee: Canon Kabushiki Kaisha
G06N20/00G06F16/11G06F16/21G06F16/24578G06F16/285G06F16/3323G06F16/35G06N3/0454G06N3/08G16H40/20G16H50/20
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Quick Facts
Patent No.
US 11,636,378
App. No.
16/113,861
Granted
Apr 25, 2023
Kind
B2
Abstract

An information processing apparatus includes an itemized reliability level calculation unit configured to calculate a first reliability level, wherein the first reliability level is a reliability level of classification target data, and a second reliability level, wherein the second reliability level is a reliability level of a label associated with the classification target data, a learning data reliability level calculation unit configured to calculate a learning data reliability level of learning data including the classification target data and the label based on the first reliability level and the second reliability level, and a classification model learning unit configured to formulate a classification model for giving a label to desired classification target data based on plural pieces of learning data and learning data reliability levels.

Claims (24)

1. An information processing apparatus comprising:

one or more processors; and

at least one memory storing instructions executable by the one or more processors to perform operations comprising:

calculating a first reliability level, wherein the first reliability level is a reliability level of classification target data, and a second reliability level, wherein the second reliability level is a reliability level of a label associated with the classification target data, and wherein the first reliability level and the second reliability level are different from each other;

calculating a learning data reliability level of learning data including the classification target data and the label based on the first reliability level and the second reliability level; and

formulating a classification model for giving a label to desired classification target data based on plural pieces of learning data and learning data reliability levels.

2. The information processing apparatus according to claim 1 , the operations further comprising:

calculating a third reliability level, wherein the third reliability level is a reliability level of information about an association between the classification target data and the label; and

calculating the learning data reliability level based on the third reliability level.

3. The information processing apparatus according to claim 1 , wherein the calculating the first reliability level comprises calculating the first reliability level of the classification target data based on information about the classification target data included in the learning data.

4. The information processing apparatus according to claim 3 , wherein the information about the classification target data includes information about a creator or a provider of the classification target data included in the learning data.

5. The information processing apparatus according to claim 1 , wherein the calculating the second reliability level comprises calculating the second reliability level of the label based on information about the label included in the learning data.

6. The information processing apparatus according to claim 5 , wherein the information about the label includes information about a creator or a provider of the label included in the learning data.

7. The information processing apparatus according to claim 1 , wherein the calculating the first reliability level and the second reliability level comprises calculating, based on information about a creation or acquisition method of respective items included in the learning data, the first reliability level or the second reliability level of the items.

8. An information processing method comprising:

calculating a first reliability level, wherein the first reliability level is a reliability level of classification target data, and a second reliability level, wherein the second reliability level is a reliability level of a label associated with the classification target data, and wherein the first reliability level and the second reliability level are different from each other;

calculating a learning data reliability level of learning data including the classification target data and the label based on the first reliability level and the second reliability level; and

formulating a classification model for giving a label to desired classification target data based on plural pieces of learning data and learning data reliability levels.

9. An information processing system comprising:

one or more processors; and

at least one memory storing instructions executable by the one or more processors to perform operations comprising:

calculating a first reliability level, wherein the first reliability level is a reliability level of classification target data, and a second reliability level, wherein the second reliability level is a reliability level of a label associated with the classification target data, and wherein the first reliability level and the second reliability level are different from each other;

calculating a learning data reliability level of learning data including the classification target data and the label based on the first reliability level and the second reliability level; and

formulating a classification model for giving a label to desired classification target data based on plural pieces of learning data and learning data reliability levels.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 7, 2018
From: MATSUKI, NAOKI
To: CANON KABUSHIKI KAISHA
Reel/Frame 047701/0015 →
Priority Claims (1)
JP JP2017-167258 · Aug 31, 2017 · national
Continuity (1)
Related Publication 20190065996A1 · Feb 28, 2019