One of your tasks at work is to train a model using sentences with the correct word context (i.e., words in a sentence following a meaningful and correct order). However, to train such model, you also need to create a dataset of words used in an incorrect context. You can think of this task as a version of Negative Sampling - a neat technique for training the famous Word2Vec model. Concretely, in this challenge you will create a workflow that takes a sentence and scrambles the order of its words. You can create a small sample of sentences to test your work with the Table Creator node.
Input
I like cats.
Output
cats. like I
Hint: Our simple solution only uses 5 nodes, but the permutations are not exactly random. Conversely, our more complex solution uses more than 15 nodes and 2 loops, as well as the Random Numbers Generator node, to create truly scrambled sentences. Bonus: Create a solution with true randomization without using any loops.
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
Download WorkflowDeploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.
Try NodePit Runner!Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to mail@nodepit.com.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.