Building an ontology for eldercare service in China with a hierarchical clustering method

Abstract

With the rapidly aging population in various countries worldwide, providing services for the elderly becomes a problem that human beings cannot ignore. To solve the problem of the messy names of these services, this paper proposes a semi-automatic method of constructing an ontology of elderly services based on hierarchical clustering by researching ontology construction ideas and methods in many fields. We crawl the names of the elderly services from government websites and multiple elderly service companies’ websites and crawl the interpretation of each service using Google searches. The weight value of each participle for this care name is given by word segmentation and frequency statistics of the paraphrase, each care name was constructed into a word vector, and a K-means clustering algorithm is used to cluster various elderly care services. Finally, under the guidance of experts, the ontology model of elderly services is finally constructed; this model lays the foundation for the integration research of the elderly service industry.