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A Machine Learning Sentiment Analyzer Based on Natural Language Parsing Tree

A syntactic parse tree, parser technology, applied in natural language data processing, instruments, computer parts, etc.

Active Publication Date: 2019-04-05
SHANGHAI JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the defects or improvement needs of the prior art, the present invention provides a machine learning sentiment classifier based on the natural language syntactic analysis tree, the purpose of which is to solve the existing The relationship between vocabulary and grammatical structure that cannot be reflected in sentiment analysis technology, and the characteristics of each vocabulary part of speech

Method used

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  • A Machine Learning Sentiment Analyzer Based on Natural Language Parsing Tree
  • A Machine Learning Sentiment Analyzer Based on Natural Language Parsing Tree
  • A Machine Learning Sentiment Analyzer Based on Natural Language Parsing Tree

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Embodiment Construction

[0062] The emotion analyzer of the present invention mainly includes two parts, syntactic analysis of natural language and machine learning based on grammatical features.

[0063] Among them, the syntactic analysis of natural language is to build a natural language grammatical analyzer for various knowledge of natural language, which can extract the text part of speech, text grammatical features, and text dependencies in natural language. In this system, using the CRF (Conditional random fields: conditional random field) method, compared with the current general HMM (Hidden Markov Model: Hidden Markov Model), CRF can realize the association between the current vocabulary and global information, instead of The grammatical analysis matching is only limited to part of the information, which greatly increases the analysis ability of the grammatical analyzer.

[0064] Machine learning based on grammatical features is a method of machine learning using the syntactic features extract...

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Abstract

The invention discloses a machine learning sentiment analyzer based on a natural language syntax analysis tree, which includes a syntax analysis module and a machine learning module, and the syntax analysis module includes a CRF model analyzer, an LALR syntax analyzer, a feature analyzer and a syntax tree generator , wherein the feature analyzer also includes a part-of-speech analysis module, a grammatical component analysis module and a lexical dependency analysis module, and the machine learning module includes a machine learning model and a machine learning emotional result fusion module.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, in particular to a machine learning sentiment analyzer based on natural language syntax analysis tree. Background technique [0002] Web has increasingly become the carrier of various information in modern society. With the rise and popularity of Web 2.0, more and more texts are actively published by ordinary users, such as news, blog posts, product reviews, forum posts and so on. Sentiment analysis is to effectively analyze and mine these information to identify their emotional trends—happy, sad, or whether their opinions are "agree" or "disagree", and even the evolution of emotions over time. In this way, we can better understand the consumption habits of users, analyze the public opinion of hot events, and provide important decision-making basis for enterprises, governments and other institutions. [0003] However, the current general information retrieval technology, especia...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/27G06K9/62
CPCG06F40/211G06F40/253G06F40/284G06F18/2411G06F18/24155G06F18/2415
Inventor 唐新怀蒋戈胡月胡晓博施维
Owner SHANGHAI JIAOTONG UNIV
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