graykode / graykode/nlp-tutorial

Which kind of model is better for keyword-set classification?

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Description

There exists a similar task that is named text classification.

But I want to find a kind of model that the inputs are keyword set. And the keyword set is not from a sentence.

For example:
```
input ["apple", "pear", "water melon"] --> target class "fruit"
input ["tomato", "potato"] --> target class "vegetable"
```
Another example:
```
input ["apple", "Peking", "in summer"] --> target class "Chinese fruit"
input ["tomato", "New York", "in winter"] --> target class "American vegetable"
input ["apple", "Peking", "in winter"] --> target class "Chinese fruit"
input ["tomato", "Peking", "in winter"] --> target class "Chinese vegetable"
```

Thank you.

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Piste de recherche

The issue names no file, test, or entry point. Start by reviewing the referenced text-classification material and clarify how keyword sets should be represented and evaluated; the work is complete when a specific model direction and implementation scope are agreed.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Évaluation

Domaine
machine-learning
Type d'issue
Fonctionnalité
Difficulté
5/5
Temps estimé
Plus d'une semaine
Activité
À l'abandon
Clarté
À clarifier
Accessibilité débutants
20/100

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