Biblio
This article shows the analogy between natural language texts and quantum-like systems on the example of the Bell test calculating. The applicability of the well-known Bell test for texts in Russian is investigated. The possibility of using this test for the text separation on the topics corresponding to the user query in information retrieval system is shown.
Our operational context is a task-oriented dialog system where no single module satisfactorily addresses the range of conversational queries from humans. Such systems must be equipped with a range of technologies to address semantic, factual, task-oriented, open domain conversations using rule-based, semantic-web, traditional machine learning and deep learning. This raises two key challenges. First, the modules need to be managed and selected appropriately. Second, the complexity of troubleshooting on such systems is high. We address these challenges with a mixed-initiative model that controls conversational logic through hierarchical classification. We also developed an interface to increase interpretability for operators and to aggregate module performance.