Sorry for the slow response, it's been internet years 8-)
We have an update coming for User Modeling (to be announced soon). After that update, such a gibberish post will return an error.
User Modeling is based on word counting. Users should ensure that their input is actually from a human and intelligible. The service looks for certain words in the input, and will reject input that doesn't have enough of those words for the service to estimate characteristics. In the upcoming release, the documentation will explain how this works and what the relevant words are.
Also, we will provide a measurement of how accurate our results are based on the number of words that are in the input. This should allow users to understand the reliability of the results in the context of their application (e.g. a casual movie recommender app might be ok with very low confidence, while an application that makes more critical recommendations might require higher confidence).
We have an update coming for User Modeling (to be announced soon). After that update, such a gibberish post will return an error.
User Modeling is based on word counting. Users should ensure that their input is actually from a human and intelligible. The service looks for certain words in the input, and will reject input that doesn't have enough of those words for the service to estimate characteristics. In the upcoming release, the documentation will explain how this works and what the relevant words are.
Also, we will provide a measurement of how accurate our results are based on the number of words that are in the input. This should allow users to understand the reliability of the results in the context of their application (e.g. a casual movie recommender app might be ok with very low confidence, while an application that makes more critical recommendations might require higher confidence).