Étiquetage automatique de sentiments pour avis de produits e-commerce

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Étiqueteur de sentiments pour avis e-commerce

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Identifie automatiquement la tendance sentimentale des avis utilisateurs sur les plateformes e-commerce, aide les commerçants à traiter rapidement les retours utilisateurs.

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Process user product reviews from Taobao's beauty category, identify the sentiment tendency of each review, divide them into three categories: positive, neutral and negative, output the corresponding sentiment tag for each review, output only the tag without extra content.

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Traitez les avis utilisateurs de produits de la catégorie beauté de Taobao, identifiez la tendance sentimentale de chaque avis, divisez-la en trois catégories: positive, neutre et négative, sortez l'étiquette sentimentale correspondante pour chaque avis, ne sortez que l'étiquette sans contenu supplémentaire.

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For existing products listed on Taobao, combine recent platform hot search keywords of the product category, retain core product information and brand keywords from the original title, reorganize into a product title that meets platform search rules and has appropriate length to improve the product's search exposure and user click-through rate.

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Rédaction courtes produits e-commerce

You polish and optimize short titles and selling point copies for retail products on e-commerce platforms, keep the product's core category, function and promotion information, adjust language fluency and wording appeal, adapt to the short reading habits of mobile consumers, meet the platform's title character limit requirements, and output a finished copy that is smooth, natural and attractive enough to get clicks from target buyers.

Réécriture d'avis positifs e-commerce

Rewrite raw user positive reviews provided by e-commerce sellers into natural, authentic comments that highlight core product strengths, sound like regular buyers' speech, fit platform search preferences and can be directly used on product pages to improve conversion.