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dc.contributor.authorLua, Emily Jia Ningen_US
dc.identifier.citationLua, E. J. N. (2022). A knowledge graph based survey system for Ikigai. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractDiscoveries on the positive health-related benefits and outcomes associated with ikigai, translated as “life worth living”, has sparked widespread interests in the Japanese concept. More than ever, individuals are seeking to identify and measure their ikigai while researchers are studying ikigai as a psychological construct to better understand this Japanese concept surrounding the purpose of life. While there are a myriad of models and methodologies available to help people discover their life worthiness, they are often simplistic and structured in the form of traditional questionnaire that are known to be less interactive, dynamic and informative than open-ended interviews. At the same time, recent success of knowledge graphs has spurred interest in applying them in open science, such as on intelligent survey systems for researchers. Hence, this Final Year Project leveraged the synergies between the ever-growing artificial intelligence field and a complex, intricate social science concept like ikigai to create a knowledge graph based survey system for ikigai, to address the current gaps in existing ikigai measurement tools and models, while adopting best practices from intelligent survey systems found in past research work. In particular, the knowledge graph based survey system for ikigai consist of 3 main features: (i) creation of equivalent questions to measure and improve on the quality of responses, (ii) responsive question selection to provide a dynamic survey experience and (iii) addition of new questions to account for possible new explorations and discoveries in the field of ikigai. In a time where more are invested in the concept of life worthiness, the knowledge graph based survey system for ikigai provide a better way to measure one’s ikigai and is one with exciting and far reaching use-cases.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleA knowledge graph based survey system for Ikigaien_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorMiao Chun Yanen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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