Text-Item Vectorization Task
(Redirected from extract numerical features from text content)
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A Text-Item Vectorization Task is a vectorization task that accepts text items.
- Context:
- Input: Text Items.
- output: Text Item Vectors.
- It can range from (typically) being a Data-Driven Text Item Vectorization Task (such as corpus-based vectorization) to being a Heuristic Text Item Vectorization Task.
- Example(s):
- See: Text Item Vectorization System.
References
2014
- http://scikit-learn.org/stable/modules/feature_extraction.html#the-bag-of-words-representation
- QUOTE: Text Analysis is a major application field for machine learning algorithms. However the raw data, a sequence of symbols cannot be fed directly to the algorithms themselves as most of them expect numerical feature vectors with a fixed size rather than the raw text documents with variable length.
... the most common ways to extract numerical features from text content.
- QUOTE: Text Analysis is a major application field for machine learning algorithms. However the raw data, a sequence of symbols cannot be fed directly to the algorithms themselves as most of them expect numerical feature vectors with a fixed size rather than the raw text documents with variable length.