Topic Classification – Bridging Topic Modelling and Text Classification
Processing human language is a wide field with many aspects that can be of interest. One of such aspects is to find out the actual topic that a piece of written text is writing about. For example, if we have a text written about a match between FC Barcelona and Manchester United, we may be interested in finding out that the actual topic is football, even though the particular word football is not used in the text.
This is in fact a form of text classification and should not be mistaken with topic modeling. In the latter, we are conceptually looking for latent words that are in the text that best describe what the text is about. For topic modeling, we usually need more evidence in the text and we cannot tell beforehand what the outcome will be, because it is subject to the actual text’s content. In practical settings, aggregating over topic modeling to find common topics is something that is hence not straightforward.
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