Semantic Shopping: A Literature Study

The digitalization of the economy and society overall has a significant impact on customers’ shopping behavior. After being conditioned by experiences in entertainment or simple Internet search, customers increasingly expect that a smart shopping assistant understands his/her shopping intentions and transfers these to shopping recommendations. Thus, the emerging opportunity in this context is to facilitate an intention-based shopping experience similar to the way semantic search engines provide responses to enquiries. In order to progress this new area, we differentiate alternative types of shopping intentions to provide the first set of conversation patterns. Grounded in the Speech Act Theory and a structured literature review, semantic shopping is defined and different types of shopping intentions are deduced

A decision-making tool for real-time prediction of dynamic positioning reliability index

PhD ThesisThe Dynamic Positioning (DP) System is a complex system with significant levels of integration between many sub-systems to perform diverse control functions. The extent of information managed by each sub-system is enormous. The sophisticated level of integration between sub-systems creates an array of possible failure scenarios. A systematic analysis of all failure scenarios would be time-consuming and for an operator to handle any such catastrophic situation is hugely demanding. There are many accidents where a failure in a DP system has resulted in fatalities and environmental pollution. Therefore, the reliability assessment of a DP system is critical for safe and efficient operation. The existing methods are time-consuming, involving a lot of human effort which imposes built-in uncertainty and risk in the system during complex operation. This thesis has proposed a framework for a state-of-the-art decision-making tool to assist an operator and prevent incidents by introducing a new concept of Dynamic Positioning – Reliability Index (DP-RI). The DP-RI concept covers three phases, leading to technical suggestions for the operator during complex operations, which are defined as Data, Knowledge, Intelligence, and Action. The proposed framework covers analytics including descriptive, diagnostic, predictive and prescriptive analytics. The first phase of the research involves descriptive and diagnostic analytics by performing big data analytics on the available databases to identify the sub-systems which play critical roles in DP system functionality. The second phase of the research involves a novel approach where predictive analytics are used for the weight assignment of the sub-systems, dynamic reliability modelling and offline and realtime forecasting of DP-RI. The third phase introduces innovative prescriptive analytics to provide possible technical solutions to the operator in a short time during failures in the system to enable them to respond quickly and prevent DP incidents. Thus, the DP-RI acts as an innovative state-of-the-art decision-making tool which can suggest possible solutions to the DPO by using analytics on the knowledge database. The results proved that it is a useful tool if implemented on an actual vessel with diligent integration with the DP control system.Singapore Economic Development Board (EDB) and DNV GL Singapore Pte Ltd