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Consumer review analysis
Mining the core ideas in comments, comprehensively understanding consumers' thoughts and feelings, and helping enterprises quickly build a data analysis system based on comments. Make clear the direction of product and service improvement through the summary and induction of comments, and build a solid foundation for building a good reputation of the enterprise
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Function introduction
Scheme architecture
Application scenarios
Technical features
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Function introduction
Collocation dictionary mining
The machine automatically mines common collocation descriptions from the original comments, generates opinion collocation dictionaries in the form of dimension words+descriptors, and quickly generates machine learning samples for model customization through a small amount of secondary expansion and modification by users
Comment extraction
Accurately extract all the core ideas contained in the user's original comments, which can support the optimization of online model effects, and help enterprises understand consumers' ideas and suggestions in a deep and multi-dimensional way
Automatic classification of positive/negative comments
According to the original comments or opinions, conduct consumer subjective emotion analysis, and automatically divide them into favorable or negative comments to help enterprises accurately grasp consumer satisfaction
Custom opinion classification
Based on a small amount of annotated data, it can achieve user-defined classification of comments, help enterprises automatically summarize various views, efficiently summarize feedback information, and more specifically improve product services and quality
Scheme architecture
Scheme composition and use process
Mining customization through comment matching can quickly realize the scene based business demands of view extraction, view classification, emotion classification, etc. of customer comments, and help significantly improve the accuracy and effect of landing scenarios
Comment opinion extraction API
Automatically extract and analyze comment content to help you achieve public opinion analysis, user understanding, and support product optimization and marketing decisions View details
Emotional Orientation Analysis API
For Chinese text with subjective description, the emotional polarity category of the text is automatically judged and the corresponding confidence level is given. Emotional polarity is divided into positive, negative and neutral View details
Application scenarios
After sales service improvement
The machine analyzes the comment content of Gome e-commerce in real time, extracts the negative views expressed by users, and automatically classifies them according to the dimensions of content expression, so as to help improve product services and enhance service reputation
Cooperation cases
Gome Online
Technical features
Low training cost
Just provide unsupervised corpus, you can automatically learn deep semantic and syntactic features, build comment collocation dictionary, and directly adapt it to comment opinion extraction and opinion emotion analysis
Strong scene adaptability
It supports comment analysis in various e-commerce scenarios. The algorithm has strong migration learning and adaptability to field scenarios, with an overall accuracy rate of more than 90%
Comment classification can be customized flexibly
Users can customize the opinion classification system, and only need to provide some weak supervision data to train and obtain the ability of opinion classification
Deep semantic computing capability
Use an automated opinion matching dictionary, based on Baidu natural language processing deep semantic matching technology and Baidu big data, to achieve highly accurate and highly recalled comment opinion output results
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Related recommendations
Analysis of emotional tendency
Automatically judge the emotional orientation of texts containing subjective information, and provide basic technical support for applications such as word-of-mouth analysis, topic monitoring, public opinion analysis, etc
Comment extraction
Automatically extract and analyze comments to help you achieve public opinion analysis, user understanding, and support product optimization and marketing decisions
Text review
Judge whether a paragraph of e-commerce comment text conforms to the online document sending standard, realize automatic and intelligent text review, and greatly save the labor cost of content review
Technical capability
Voice technology
Character recognition
Face and Human Body
Image technology
Language and knowledge
video technique
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Scenario application
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