Towards Knowledge-based Smart Service Systems: The Case of a Recommender System for a Cultural Organization

Abstract

Big data and artificial intelligence (AI) lead to a revolution that transforms conventional enterprises into data-driven organizations in which knowledge discovered from big data and processed by AI techniques will be integrated into traditional knowledge in order to provide smart services to business users. Consequently, a major concern is how to design and develop a knowledge-based smart service system for supporting AI-based applications. This paper proposes an approach for elaborating a knowledge-based smart service system and demonstrates the approach with a case study about a knowledge-based smart service system for a cultural organization. The proposed approach includes different layers such as Data-as-a-Service, Information-as-a-Service, Knowledge-as-a-Service, and Insight-as-a-Service.

From Diagnosis to Melioration of Sustainable Development in SMEs: The SME-Sustainability Compass

“…In the manner of a recommender system [11] such as Netflix 3 type systems, the SME that completes the questionnaire would receive website links from SMEs (2-3) that are champions in their sustainability profile and have similar characteristics with respect to several other variables. These champions would become models for SMEs to emulate and implement practices and processes inspired by similar SMEs.…”

“…Demographic data contain data related to the characteristics of SMEs. Diagnostic data is data extracted from the previous diagnostic system in order to overcome the challenge of cold start, which is defined as the insufficient amount of data input for the development of recommendation services [11]. Open data and third-party data help the SME-SC to capture different types of knowledge related to the sustainability development of SMEs.…”

“…Descriptive analytics is the examination of data that can be used to identify business profiles. Predictive analytics makes recommendations using historical data combined with data mining techniques and machine learning [11].…”

“…Concerning the management dimension, context recognizing identifies the context based on the business situation of the SME [11]. On the other hand, context reasoning understands specifically the situation, along with how it fits the overall business context of the whole ecosystem, and then determines the corresponding knowledge related to a similar context in the knowledge base to make specific recommendations for the SME [11].…”

Enabling Business Analytics in SMEs: The Trivi Open-source System

“…The GUI components deal with displaying business insights through interactive actionable dashboards, tables, or charts [1] [10]. The API services are typically invoked from other applications, whereas the GUI components are typically used to serve end users such as managers.…”