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Method for identifying basic noun phrases of Lao language based on laminated combined classifier

A technology of noun phrases and recognition methods, applied in the direction of text database clustering/classification, instruments, unstructured text data retrieval, etc. The effect of improving accuracy

Inactive Publication Date: 2019-10-22
KUNMING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved in the present invention is to provide a method for identifying basic noun phrases in Lao language based on a stacked combination classifier, which is used to solve the problem of identifying basic noun phrases in Lao language

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  • Method for identifying basic noun phrases of Lao language based on laminated combined classifier
  • Method for identifying basic noun phrases of Lao language based on laminated combined classifier
  • Method for identifying basic noun phrases of Lao language based on laminated combined classifier

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Embodiment 1

[0019] Embodiment 1: as figure 1 As shown, a Lao language basic noun phrase recognition method based on a stacked combination classifier, the specific steps are as follows:

[0020] Step1, obtain the basic noun phrase corpus of Lao language. The basic noun phrase corpus of Lao language is passed through the word segmentation and part-of-speech tagging system, and Lao students manually mark the basic noun phrases of Lao language. The basic nouns are defined as no smaller noun phrases inside. According to the Lao grammar, Lao The base noun phrase (BaseNP) form is as follows:

[0021] 1. BaseNP→BaseNP+BaseNP

[0022] 2.BaseNP→BaseNP+adjective

[0023] 3. BaseNP→BaseNP+verb

[0024] 4.BaseNP→BaseNP+ quantifier

[0025] 5. BaseNP→BaseNP+ refers to the pronoun

[0026] 6. BaseNP→BaseNP+ subject-predicate structure

[0027] 7. BaseNP→BaseNP+ preposition structure

[0028] 8.BaseNP→BaseNP+refers to pronoun+adjective

[0029] 9.BaseNP→BaseNP+adjective+quantifier

[0030] 10.B...

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Abstract

The invention discloses a method for identifying basic noun phrases of Lao language based on a laminated combined classifier, and belongs to the field of natural language processing. The method is a basic service in natural language processing, and mainly fuses old rattle linguistic features into an algorithm model, a method of a combined classifier is selected, the recognition precision is improved, and the selected algorithm model is CRF + SVM. The method comprises the following steps: firstly, respectively labeling by using three identification models of CRF, SVM forward and SVM reverse; obtaining three different prediction results and forming a new data set together with an original data set, then selecting a model with the highest sequence labeling performance as an upper-layer classification algorithm, finally using the new data set, using words, part-of-speech and three model classification results as features and sent to an upper-layer model, and using an identification resultof the upper-layer model as a final result. The method is high in recognition accuracy of the basic noun phrases of the Lao language, and has certain research significance.

Description

technical field [0001] The invention relates to a Lao language basic noun phrase recognition method based on a stacked combination classifier, which belongs to the field of small and medium language recognition in natural language processing. Background technique [0002] Basic noun phrase recognition is an important basic task of natural language processing. Noun phrases exist in large numbers in sentences and often play important syntactic roles such as subject and object. Therefore, its accurate recognition plays a key role in simplifying the sentence structure for further grammatical analysis. . The current research on noun phrases is mainly divided into statistical-based recognition methods and rule-based recognition methods, and focuses on the recognition of basic noun phrases and longest noun phrases. The present invention uses three recognition models of CRF, SVM forward and SVM reverse to mark respectively, obtains 3 different prediction results, and forms a new da...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06F16/35
CPCG06F16/355G06F16/353G06F40/289
Inventor 周兰江汤礼欣张建安
Owner KUNMING UNIV OF SCI & TECH