Using KNIME to build a news bot with machine learning

Hello everyone,

I have been using KNIME as a journalist to automotive the cleaning of large datasets in recent months. However, I have been intrigued if I could use KNIME to build a bot to write news stories using machine learning. Among my routine tasks, I have to write stories about corporate earning results. I know organizations like AP, Bloomberg, and Reuters use machine learning to automotive this work.

I’m new to the world of coding and data science. Might the community be kind to guide if I could build an application like this using KNIME? If it is possible, could the community please recommend me some learning material to kickstart this project?

Thank you for your time and kind help,

Cheers,

Daniel

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For text generation there is a blog post https://www.knime.com/blog/use-deep-learning-to-write-like-shakespeare

And also some examples on hub.knime.com:
https://hub.knime.com/search?q=text%20generation

I’m afraid we do not have any self-study contents available on this topic, but there are various MOOC available. https://www.kdnuggets.com/ is a great resource when you are looking for freely available ML/DS learning content. Lately they featured Stanford’s Natural Language Processing with Deep Learning (CS224n).

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Hello Marten, thank you for your time and for sharing this information. As I’m new in this world I didn’t know the name of the concepts I’m trying to apply. This material is a great starting place. I will put hands to work. Cheers,

Dear KNIME community,

I have continued doing some research and I was able to understand a bit better what I’m trying to do. The branch of machine learning I have to learn to execute this project is natural language generation using structured data. Some people also call it data-to-text generation. Here is a small paper on this area: https://mc.ai/natural-language-generation-from-structured-data/.

I searched in the forum and the KNIME website and I couldn’t find any guides about these concepts. I don’t know if there are any other names for this concept.

Cheers,

Daniel

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