I am new to KNIME and trying to categorize/group a column of text (see attached csv). For example, row 4, 5, 6, 13 are 'price' related. Row 11 is price related as well but the exact word is not there. Attached is my attempt so far. It seems nGram with 3 words is creating meaningful theme. I think I need to group relevant themes after nGram node. For example, price related themes, customer support related theme etc.
I would highly appreciate any assistance please.
have you tried classifying the documents / rows with the classes "price related", "not price related"? You can use the ngrams a features. However, I suggest to filter them before and use only the frequent ones. Otherwise you would end up with a huge feature space. Here is an example of how to use ngrams as features in classification: https://www.knime.com/blog/sentiment-analysis-with-n-grams.
I hope this helps.
Thanks Kilian, much appreciated.
Hi I am struggling in data categories volume of the data is 95 cent “no” cases and 5 cent “yes”. Here my keen area is that I have to concentrate on 5 cent and I have to get 99cent then only will model can be ready please help
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