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.
Contributor guide
Research direction
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.
Written by the indexing model from the issue text.
Assessment
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100