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【2020 Solutions】 'Knowledge Graphs' create health education angels, answering all questions faced during pregnancy

Artificial Intelligence (AI) is evolving rapidly. Traditional scripted response smart customer services are no longer sufficient. Emerging from this is the use of Knowledge Graphs in smart assistants. Through knowledge graphs, these smart assistants can provide exhaustive, tailored customer service, helping consumers efficiently and effortlessly find their desired products. The most common AI applications in daily life are smart customer services or smart assistants. For smart customer services, the aim is mainly to address customer inquiries, but they often face the issue of providing too generic and rigid responses, lacking flexibility.

Utilizing knowledge graphs to establish smart assistants

To develop a smooth-questioning smart assistant, it's crucial to optimize technologies such as natural language processing, semantic analysis engines, multi-turn dialogues, context awareness, emotion recognition, and personalization. Supported by the Economic Ministry's Technology Department, the Institute for Information Industry’s Service Innovation Research Institute has developed tools for domain knowledge construction and management. These tools assist in transforming corporate websites, databases, and documents into corporate knowledge graphs using AI recognition models. When used in smart customer service, if the customer query is vague, it can proactively ask follow-up questions based on the knowledge graph and provide precise answers through multiple dialogue rounds, saving on professional labor costs and response time, and delivering better consumer service experiences. Chen Bing-Yi, head of the Institute, points out that simple smart assistants operate by connecting to fixed APIs and responding based on predefined data formats, which is straightforward for queries like tracking shipments through Line or Facebook Messenger. However, for more flexible customer issues such as cancer insurance clauses, credit card application terms, or legal advice, more complex technologies are required. Technically, AI must convert unstructured data from documents, websites, or even social media into patterns that computers can understand, i.e., establishing corporate knowledge graphs. In simple terms, knowledge graphs are primarily built by extracting all significant texts and marking the relationships between them, automatically creating relational graphs among all individuals, events, and objects. For example, the computer can extract and determine the relation between Nantou and Oolong Tea as 'Origin' from social data, and link 50 Lan's products to Oolong Tea as 'Product'. Once a consumer wishes to know 'Where does 50 Lan’s Oolong tea come from?', the system can infer using the knowledge graph and provide 'Nantou' as the response, making customer service smarter and more professional. Additionally, smart assistants no longer passively receive queries; they can actively notify and remind consumers, for instance, notifying pregnant women of important prenatal tests they need to undergo through Line and Facebook Messenger, ensuring no tests are missed and enhancing safety. The smart assistants developed by the Institute are being progressively applied across retail, finance, and medical sectors including applications such as querying credit card benefits, product specifications, and medical education advice, with several companies already having successfully implemented these practices. Plans are in place to integrate external social data or open up knowledge graphs for future development, continuing to collaborate with partners to advance the application of knowledge graphs in various new forms of AI services.

Applications of Knowledge Graphs: Health Education Angel Chatbot

New mothers often face a multitude of questions during pregnancy, such as morning sickness, diet, fetal health, and prenatal check-up considerations, affecting their sleep, personal health, and potentially impacting fetal health. The Service Innovation Research Institute, in collaboration with Hua Xin Health Technology, uses AI technology to process health education manuals from the Ministry of Health and Welfare and community discussion articles. This initiative aims to build a Health Education Angel using natural language processing and knowledge graph technologies specifically for addressing various issues encountered during pregnancy.

The institute and Hua Xin Health Technology have collaborated to develop the Health Education Angel chatbot to answer various questions during pregnancy.

▲ The institute and Hua Xin Health Technology have collaborated to develop the Health Education Angel chatbot to answer various questions during pregnancy.

If there are questions related to prenatal examinations, they can be inquired through 'Prenatal Examination ABC', where the system will provide information about whether certain prenatal tests are chargeable and the diseases they can screen for. If there are concerns regarding dietary and health status during pregnancy, 'Pregnancy Encyclopedia' can be utilized. By posing questions in natural language, the system will offer the most relevant expert answers. Additionally, information about valuable pregnancy resources and welfare assistance is available for pregnant mothers to consult.

The Health Education Angel can pose questions in natural language, and the system will provide the most relevant expert responses.

▲ The Health Education Angel can pose questions in natural language, and the system will provide the most relevant expert responses.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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