Recommender systems are widely used in e-commerce platforms, where users regularly receive unsuitable tips, because they are based on the principle ‘suggest more of the same’. In other words: I buy a couch and get recommended another couch the next time I’m on the website.
Nowadays, the demand in industry of dialogue systems to be able to naturally communicate with industrial systems is increasing, as they allow to enhance productivity and security in these scenarios. However, adapting these systems to different use cases is a costly process, due to the complexity of the scenarios and the lack of available data.
Knowledge Graph Question Answering (KGQA) systems are based on machine learning algorithms, requiring thousands of question-answer pairs as training examples or natural language processing pipelines that need module fine-tuning.