Information processing apparatus, information processing system, information processing method, and storage medium
US-2024193370-A1 · Jun 13, 2024 · US
Natural language processing system, natural language processing method, and natural language processing program
US12585881B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12585881-B2 |
| Application number | US-202318460762-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 5, 2023 |
| Priority date | Oct 25, 2022 |
| Publication date | Mar 24, 2026 |
| Grant date | Mar 24, 2026 |
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- Title
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Abstract
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A natural language processing system including: a weight array acquisition unit that acquires a weight array related to a weight for determining a label corresponding to a character string, the weight array being generated by learning based on at least one learning character string in which a feature and a label of at least one character string including at least one character are set; a feature extraction unit that extracts a feature corresponding to a target character string; and a label determination unit that determines the label of the target character string on the basis of the learned model generated by learning, the weight array, and the extracted at least one feature.
First claim
Opening claim text (preview).
What is claimed is: 1 . A natural language processing system comprising a processor configured to: generate, by machine learning, a weight array and a learned model based on at least one learning character string in which a feature and a label of at least one character string including at least one character are set; acquire a target character string; acquire the weight array related to a weight for determining the label corresponding to the target character string; acquire modification information related to modification of a plurality of clauses corresponding to the target character string; extract a feature corresponding to at least one of a modification source clause of a target clause corresponding to the target character string and a clause that is different from the target clause and is a modification source clause of a modification destination clause of the target clause, on the basis of the modification information; and determine the label of the target character string on the basis of the learned model generated by the machine learning, the weight array, and the extracted feature. 2 . The natural language processing system according to claim 1 , wherein the label indicates an attribute corresponding to a meaning of the target character string in a character string to which the target character string belongs. 3 . A computer-implemented method for natural language processing, method comprising: generating, by machine learning, a weight array and a learned model based on at least one learning character string in which a feature and a label of at least one character string including at least one character are set; acquiring a target character string; acquiring the weight array related to a weight for determining the label corresponding to the target character string; acquiring modification information related to modification of a plurality of clauses corresponding to the target character string; extracting a feature corresponding to at least one of a modification source clause of a target clause corresponding to the target character string and a clause that is different from the target clause and is a modification source clause of a modification destination clause of the target clause, on the basis of the modification information; and determining the label of the target character string on the basis of the learned model generated by the machine learning, the weight array, and the extracted feature. 4 . A non-transitory computer-readable medium storing a natural language processing program for causing a computer to implement: generating, by machine learning, a weight array and a learned model based on at least one learning character string in which a feature and a label of at least one character string including at least one character are set; acquiring a target character string; acquiring the weight array related to a weight for determining the label corresponding to the target character string; acquiring modification information related to modification of a plurality of clauses corresponding to the target character string; extracting a feature corresponding to at least one of a modification source clause of a target clause corresponding to the target character string and a clause that is different from the target clause and is a modification source clause of a modification destination clause of the target clause, on the basis of the modification information; and determining the label of the target character string on the basis of the learned model generated by the machine learning, the weight array, and the extracted feature.
Assignees
Inventors
Classifications
- G06F40/289Primary
Phrasal analysis, e.g. finite state techniques or chunking · CPC title
- G06F40/30Primary
Semantic analysis · CPC title
Machine learning · CPC title
Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars · CPC title
- G06F40/253Primary
Grammatical analysis; Style critique · CPC title
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- What does patent US12585881B2 cover?
- A natural language processing system including: a weight array acquisition unit that acquires a weight array related to a weight for determining a label corresponding to a character string, the weight array being generated by learning based on at least one learning character string in which a feature and a label of at least one character string including at least one character are set; a featur…
- Who is the assignee on this patent?
- Nomura Res Inst Ltd
- What technology area does this patent fall under?
- Primary CPC classification G06F40/289. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Mar 24 2026 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 6 related publications on this page (citations in our corpus or others sharing the same primary CPC).