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HINCare: An Intelligent Helper Recommender System for Elderly Care

Published: 13 May 2024 Publication History

Abstract

In Hong Kong, the number of elderly citizens will reach one-third of the population within the next decade. To mitigate this problem, timebanking has received attention in recent years. In timebanking, an NGO helper earns time credits through providing voluntary services (e.g., household duties) to elders. These time credits can be used to acquire other services. Although timebanking has shown the promise of promoting mutual care in many countries, its potential has not been fully utilized, due to the lack of IT and data support. We thus develop HINCare, a software platform that supports timebanking for multiple NGOs. Besides providing convenience to NGO supervisors, helpers, and elders, HINCare makes use of a heterogeneous information network (HIN) for recommending suitable helpers to elders. This is the first time a graph-based recommender system is used for such purposes. Currently, HINCare is used by 12 NGOs to serve more than 5000 users in Hong Kong. In this demonstration, participants can play the role of helpers and elders in the HINCare environment.

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References

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Census and statistics department. https://www.censtatd.gov.hk/en/.
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    cover image ACM Conferences
    WWW '24: Companion Proceedings of the ACM Web Conference 2024
    May 2024
    1928 pages
    ISBN:9798400701726
    DOI:10.1145/3589335
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 13 May 2024

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    Author Tags

    1. elderly care
    2. heterogeneous information network
    3. recommender systems

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    WWW '24: The ACM Web Conference 2024
    May 13 - 17, 2024
    Singapore, Singapore

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