AllergyBot

Hsu, Paris; Zhao, Jingshu; Liao, Kehan; Liu, Tianyi; Wang, Chen

doi:10.1145/3027063.3049270

Cited by 25 publications

(19 citation statements)

References 1 publication

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“…The latter is used by healthcare workers to automate patient intake. Other chatbots collect information about people's diet [44] or provide restaurants with a tool to collect allergy information based on users' allergens [45]. Chatbots in education support the teaching of a variety of subjects, as English [46], Medicine [42], and business process models [47].…”

Section: A Conversational Agentsmentioning

confidence: 99%

“…Specifically, Figure 13 focuses on the odd questions (the positive ones, which should obtain a high score), while Figure 14 focuses on the even ones (the negative ones, which should obtain a low score). The users considered AIDA-Bot easy to use (with an average score of 4.47 ± 0.62 45 ) and believed that its functions were well-integrated (3.87±0.62). They claimed that it was not too complex to use (1.47±0.72) and that they would not need any help to use it in the future (1.27 ± 0.44).…”

Section: A User Studymentioning

confidence: 99%

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Integrating Conversational Agents and Knowledge Graphs Within the Scholarly Domain

et al. 2023

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In the last few years, chatbots have become mainstream solutions adopted in a variety of domains for automatizing communication at scale. In the same period, knowledge graphs have attracted significant attention from business and academia as robust and scalable representations of information. In the scientific and academic research domain, they are increasingly used to illustrate the relevant actors (e.g., researchers, institutions), documents (e.g., articles, patents), entities (e.g., concepts, innovations), and other related information. Following the same direction, this paper describes how to integrate conversational agents with knowledge graphs focused on the scholarly domain, a.k.a. Scientific Knowledge Graphs. On top of the proposed architecture, we developed AIDA-Bot, a simple chatbot that leverages a large-scale knowledge graph of scholarly data. AIDA-Bot can answer natural language questions about scientific articles, research concepts, researchers, institutions, and research venues. We have developed four prototypes of AIDA-Bot on Alexa products, web browsers, Telegram clients, and humanoid robots. We performed a user study evaluation with 15 domain experts showing a high level of interest and engagement with the proposed agent.

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Section: A Conversational Agentsmentioning

confidence: 99%

Section: A User Studymentioning

confidence: 99%

Integrating Conversational Agents and Knowledge Graphs Within the Scholarly Domain

et al. 2023

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“…As a result, even with recommendations, individuals with food allergies often still have to explicitly inquire and confirm allergic recommendations to ensure food safety. To address these burdens, Hsu et al designed AllergyBot [44], a chatbot that supports young adults to explore dining options with customized interactions. Preliminary studies also show that users consider using AllergyBot feasible, but the long-term use results remain unknown [4].…”

Section: Technologies To Support the Management Of Food Hypersensitivitiesmentioning

confidence: 99%

Avoiding Reactions Outside the Home: Challenges, Strategies, and Opportunities to Enhance Dining Out Experiences of People with Food Hypersensitivities

Nunes

Almeida

Chung

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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People with food hypersensitivities experience adverse reactions when eating certain foods and thus need to adapt their diet. When dining out, the challenge is greater as people entrust the care of their allergy, intolerance, or celiac disease, in the hands of staff who might not have enough knowledge to appropriately care for them. This interview study explored how people with food hypersensitivities avoid reactions while eating out, to inspire future digital technology design. Our findings show the social and emotional impact of food hypersensitivities and how people practically cope by investigating restaurants' safety precautions, correcting orders, or even educating restaurants' staff. We discuss our findings against the experiences of other people living with chronic conditions and offer design opportunities for digital technologies to enhance dining out experiences of people with food hypersensitivities. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI.

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“…Hence, people will have an idea about their health and have the right protection. To improve the quality of life for young adults with food allergies, AllergyBot [14] was proposed as an intelligent and humane chatbot that provides restaurants' allergy accommodation information based on users' allergens. Besides, chatbots from the business domain are also proposed to support customers and improve companies' services.…”

Section: Related Workmentioning

confidence: 99%

KBot: A Knowledge Graph Based ChatBot for Natural Language Understanding Over Linked Data

Ait-Mlouk

Jiang

2020

IEEE Access

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AllergyBot

Cited by 25 publications

References 1 publication

Integrating Conversational Agents and Knowledge Graphs Within the Scholarly Domain

Integrating Conversational Agents and Knowledge Graphs Within the Scholarly Domain

Avoiding Reactions Outside the Home: Challenges, Strategies, and Opportunities to Enhance Dining Out Experiences of People with Food Hypersensitivities

KBot: A Knowledge Graph Based ChatBot for Natural Language Understanding Over Linked Data

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