like many others, I’m also a new user of MeTA and need some help. Currently I need a tool, that is able to take a text and to generate keywords from the text. (And I actually mean from the text, not out of the text, because the actual “main” keyword might not be in the text.)
My idea was to take a deep learning algorithm like TensorFlow and train it with the data from Question / Answer sites, where the questions are tagged. But then I found the MeTA Project. And MeTA might be more helpful then a simple Deep Learning machine.
But I don’t know where I can start to extract the keywords. In the tutorial I found the frequency analysis. It’s a good tool for the beginning, but I need something better. Let me show you something on an example.
Lets imagine I have a text about Bioshock. Of course using the frequency analysis the word Bioshock would be one of the most common words. But “game” or “computer game” should also be one of the main keywords, even if “game” od “computer game” even does not appear in the text – because the machine learned by the way the text is written, that it’s a video game / or knows that Bioshock is a video game.
Is it possible to implement such keyword generation with MeTA?