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Article comment processing method and system, electronic equipment and readable storage medium

A processing method and technology of a processing system, applied in the field of item review processing method, system, electronic equipment and readable storage media, can solve the problems of low labeling efficiency and low automation of item review processing, etc.

Pending Publication Date: 2021-03-26
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the embodiments of the present invention is to provide a method, system, electronic device and readable storage medium for processing article reviews in order to overcome the defects of low automation and low labeling efficiency in the prior art.

Method used

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  • Article comment processing method and system, electronic equipment and readable storage medium
  • Article comment processing method and system, electronic equipment and readable storage medium
  • Article comment processing method and system, electronic equipment and readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0058] A method for handling item reviews such as figure 1 As shown, the processing method includes:

[0059] Step 10, constructing an attribute list of an item category;

[0060] The attribute list includes the attribute categories of all items under the item category and the corresponding attributes of each attribute category; according to the classification of an item, it can be divided into several attribute categories, and each attribute category is an item. A general term for various specification parameters, a certain attribute under a certain specification parameter, such as a display parameter is an attribute category, including brightness, screen ratio, refresh rate, scanning mode, response time, screen resolution, 3D display and other attributes.

[0061]Step 20, crawling all comment data of a target item under the item category within a preset time period;

[0062] It should be noted that data can be crawled by SKU for a single item, or by SPU for items of the sa...

Embodiment 2

[0078] The processing method of article comment in this embodiment is further improved on the basis of embodiment 1, such as figure 2 As shown, the step 60 of calculating the similarity between each attribute and the participle in the participle set specifically includes:

[0079] Step 6011, for each word-segment set, respectively convert the attribute and the word-segment in the word-segment set according to the phonetic-shaped coding rules, and generate the corresponding phonetic-shaped code;

[0080] Step 6012: Based on the edit distance calculation model, calculate the degree of similarity between the phonetic-shaped coding of the attribute and the phonetic-shaped coding of the participle in the participle set to obtain a similarity.

[0081] Each attribute can correspond to different expressions, such as screen resolution, expression A: ultra-high-definition 4K or full HD or high-definition, expression B: the video looks very clear, or more colloquial, watching movies is...

Embodiment 3

[0085] The processing method of article comment in this embodiment is further improved on the basis of embodiment 1, such as image 3 As shown, step 60 specifically includes:

[0086] Step 6021, split the word segmentation set into multiple word segmentation sub-sets;

[0087] Step 6022, multithreading simultaneously calculates the similarity of multiple word segmentation sub-sets;

[0088] Step 6023, merging the calculation results of each word segmentation sub-set;

[0089] Step 6024, obtain the frequency according to the combined calculation result.

[0090] In order to adapt to the data processing of millions and tens of millions, the word segmentation set can be split and processed according to the time dimension. Specifically, the set size can be manually set and flexibly adjusted. After processing separately, the final list can be obtained from the set statistics.

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PUM

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Abstract

The invention discloses an article comment processing method and system, electronic equipment and a readable storage medium. The processing method comprises the following steps: constructing an article category attribute list; crawling all comment data of a target article under the article category within a preset time period; performing word segmentation processing on the comment data to obtain aplurality of segmented words; performing sentiment analysis on each segmented word, and dividing the segmented words representing the same sentiment into the same segmented word set; for each segmented word set, calculating the similarity between each attribute and the segmented words in the segmented word set, and counting the frequency that the similarity is greater than a similarity threshold;and descending or ascending the attributes according to the frequency to generate an attribute evaluation list which is used for representing the evaluation of the user on the attributes of the target object. The vocabularies associated with the article attributes are extracted from the article comments, and statistics about the article attribute data is extracted, so that the evaluation, such asgood evaluation or bad evaluation, of the user on the article is obtained.

Description

technical field [0001] The invention belongs to the field of big data processing, and in particular relates to a method, system, electronic equipment and readable storage medium for processing item reviews. Background technique [0002] The automatic processing of item reviews involves cutting-edge technologies such as big data technology, machine learning, and natural language processing. Internet companies have a large amount of item review data, including data descriptions based on simple rules (such as item star ratings, bad reviews, etc.), and There are users' subjective comment data, mainly including text data, image data, etc. Currently, the processing of item comments is mainly through manual statistics, sorting item comments based on a given simple rule, and selecting comments that meet the rules as valuable references The manual analysis of the comments of the article results in the inability to fully cover the automatic analysis and processing of the item comment ...

Claims

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Application Information

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IPC IPC(8): G06F16/951G06F16/35G06F40/289G06F40/216G06K9/62G06Q30/02
CPCG06F16/951G06F16/355G06Q30/0282G06F18/22
Inventor 李一伟
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD