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Method for discovering important noun labels through machine learning and context part-of-speech

A technology of machine learning and nouns, applied in the field of Internet, can solve problems such as low learning efficiency, high cost of learning new words, and many manual interventions

Pending Publication Date: 2020-04-21
GUANGZHOU JIANHE NETWORK TECH
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AI Technical Summary

Problems solved by technology

[0008] Existing machines require a lot of manual intervention when learning new words, which will undoubtedly lead to high learning costs and low learning efficiency for new words. Therefore, we propose a method for discovering important noun tags through machine learning and contextual part-of-speech. to solve the above-mentioned problems

Method used

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Embodiment

[0035] The method for discovering important noun tags through machine learning and contextual part-of-speech includes the following steps:

[0036] S1: First, through the corpus, this corpus requires the latest articles, select the articles of the last year as the corpus, and list certain new words that have been determined with certain data, which is used to learn the most likely context of the noun "adjectives, conjunctions , verb", etc., and sort out dozens of important nouns that have been identified (such as: Huawei, Xiaomi, ZTE, etc.);

[0037] S2: Through the operation of the previous step, a batch of collating sentence patterns can be obtained, such as: "XXX was released this year", "No matter how XXX did it", "For XXX", etc., and the corresponding Different sentence patterns can lead to different probability situations;

[0038] S3: After calculating the various types of sentence patterns, these sentence patterns are applied to the specific new article content, so th...

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Abstract

The invention belongs to the technical field of Internet. The invention relates to a method for discovering important noun labels through machine learning and context part-of-speech. The method comprises the following steps: S1, determined new words with certain data are listed through corpora, wherein the corpora need the most recent article, the articles of the last year are chosen as the corpus, the corpora are used for learning adjectives, connected words, verbs and the like in previous and later texts with the most possible nouns, and dozens of determined important nouns (such as Huawei,Xiaomi, ZTE, etc.) are sorted; and S2, through the operation of the previous step, a batch of collated sentence patterns such as 'XXX publishes... in the current year', 'no matter how XXX achieves...', 'for XXX' and the like can be obtained, and meanwhile, different probability situations can be obtained by calculating different sentence patterns. According to the method, the new words can be found through machine learning with extremely low manual intervention and arrangement cost.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a method for discovering important noun tags through machine learning and contextual part-of-speech. Background technique [0002] With the rapid development of mobile Internet infrastructure and the speed of transmission, the news information that everyone comes into contact with is explosive. All kinds of news information appear in people's field of vision like a flood, but people always have limited time to watch the news. Therefore, how to quickly recommend key tags for users is a specific and urgent need. In addition, extracting key tags of articles is also a quick way to analyze user interests, and user portraits are also an important means of analysis. [0003] Another more important aspect of new word discovery is that it can capture the latest interest points of users in real time. If a new word called XXX appeared recently, if we can’t analyze this word, we can ca...

Claims

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Application Information

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IPC IPC(8): G06F16/35G06N20/00G06F40/205G06F40/289
CPCG06F16/35G06N20/00
Inventor 李森和
Owner GUANGZHOU JIANHE NETWORK TECH
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