DECiSION: Data-drivEn Customer Service InnovatiON

Abstract

The paper presents DECiSION, an innovative framework in the field of Information Seeking Support Systems, able to retrieve all the data involved in a decision-making process, and to process, categorize and make them available in a useful form for the ultimate purpose of the user request. The platform is equipped with natural language understanding capabilities, allowing the interpretation of user requests and the identification of information sources from which to independently retrieve the information needed for the sensemaking task. The project foresees the implementation of a chatbot, which acts as a virtual assistant, and a conversational recommender system, able to dialogue with the user to discover their preferences and orient their answers in a personalized way. The goal is therefore to create an intelligent system to answer autonomously and comprehensively questions posed in natural language about a specific reference domain, to support the decision-making process. The paper describes the general architecture of the framework and then focuses on the key component that automatically translate the natural language user query into a machine-readable query for the service repository.

Towards Dynamic Feature Selection with Attention to Assist Banking Customers in Establishing a New Business

“…Very similar to the human brain, data products that aim to improve the intelligent domain knowledge 50 for the decision-making process have to be able to query heterogeneous data sources. Even though, retrieval is a nec-essary process but not sufficient.…”