@@ -35,8 +35,8 @@ The above formula has two branches, because the OSDG community dataset, which ha
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@@ -35,8 +35,8 @@ The above formula has two branches, because the OSDG community dataset, which ha
| `text` | Input texts | `list` |
| `text` | Input texts | `list` |
| `top_keywords` | The number of the top keywords of texts | `int` |
| `top_keywords` | The number of the top keywords of texts | `int` |
| `diversity` | The diversity (\[0,1\]) of the top produced keywords. A high diversity score will create very diverse keyphrases/keywords compared with low diversity, which will produce very similar keywords with the respective ones using the cosine similarity method | `float` |
| `diversity` | The diversity (\[0,1\]) of the top produced keywords. A high diversity score will create very diverse keyphrases/keywords compared with low diversity, which will produce very similar keywords with the respective ones using the cosine similarity method | `float` |
| `n_gram_range` | The different lengths of keyphrases | tuple of shape (range_x,range_y) |
| `n_gram_range` | The different lengths of keyphrases | `tuple` of shape (range_x,range_y) |
| `return_association` | If set to True then returns the association of each text with the SDGs | `Boolean` |
| `return_association` | If set to True then returns the association of each text with the SDGs | `boolean` |
