Developing an Ontology to Link Housing Data for Information Retrieval

Abstract

As urbanization accelerates, there has been a significant increase in housing information and the demand for its retrieval. Nonetheless, housing data sources are numerous and scattered across various departments and platforms, with inconsistent formats and ambiguous semantics. Meanwhile, housing-related knowledge is not systematically organized, resulting in retrieval difficulties and reduced efficiency. This paper constructs a housing domain ontology that encompasses relevant information on people, locations, organizations, residential communities, construction projects, and normative documents. It correlates housing-related data through entities, relationships, and properties, and establishes a structured, semantic knowledge system within the housing domain. Subsequently, leveraging the advantages of knowledge graphs in integrating heterogeneous data and preserving semantic associations, this paper collects housing data examples from specific regions and cities to establish a knowledge graph for information retrieval verification. The results indicate that it can effectively assist housing information seekers in fulfilling specific requirements, such as housing source searches, construction project overviews, and housing policy queries.