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ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2025,3,3]]},"abstract":"<jats:p>WiFi received signal strength (RSS) environment evolves over time due to the movement of access points (APs), AP power adjustment, installation and removal of APs, etc. We study how to effectively update an existing database of fingerprints, defined as the RSS values of APs at designated locations, using a batch of newly collected unlabelled (possibly crowdsourced) WiFi signals. Prior art either estimates the locations of the new signals without updating the existing fingerprints or filters out the new APs without sufficiently embracing their features. To address that, we propose GUFU, a novel effective graph-based approach to update WiFi fingerprints using unlabelled signals with possibly new APs. Based on the observation that similar signal vectors likely imply physical proximity, GUFU employs a graph neural network (GNN) and a link prediction algorithm to retrain an incremental network given the new signals and APs. After the retraining, it then updates the signal vectors at the designated locations. Through extensive experiments in four large representative sites, GUFU is shown to achieve remarkably higher fingerprint adaptivity as compared with other state-of-the-art approaches, with error reduction of 21.4% and 29.8% in RSS values and location prediction, respectively.<\/jats:p>","DOI":"10.1145\/3712277","type":"journal-article","created":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T12:10:14Z","timestamp":1741090214000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Graph-based Fingerprint Update Using Unlabelled WiFi Signals"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4480-1868","authenticated-orcid":false,"given":"Ka Ho","family":"Chiu","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7287-3879","authenticated-orcid":false,"given":"Handi","family":"Yin","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1810-7071","authenticated-orcid":false,"given":"Weipeng","family":"Zhuo","sequence":"additional","affiliation":[{"name":"Guangdong Provincial\/Zhuhai Key Laboratory of IRADS, and Department of Computer Science, BNU-HKBU United International College, Zhuhai, Guangdong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4778-8996","authenticated-orcid":false,"given":"Chul-Ho","family":"Lee","sequence":"additional","affiliation":[{"name":"Texas State University, San Marcos, Texas, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4207-764X","authenticated-orcid":false,"given":"S.-H. 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