Abstract
Indoor positioning data is of high significance to many indoor location-based services whereas it is of low quality due to the limitations of indoor positioning technologies. Thus, our work is focused on cleansing indoor positioning data to enhance its quality significantly. In this paper, we first introduce the data quality issues consisting in indoor positioning data and propose a cleansing framework to handle such issues. Subsequently, we formulate four specific research questions in order to settle related quality issues. In addition, we present promising methodologies and comprehensive evaluation criteria to resolve our proposed research questions.
| Original language | English |
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| Title of host publication | Proceedings - 2022 23rd IEEE International Conference on Mobile Data Management, MDM 2022 |
| Number of pages | 3 |
| Publisher | IEEE |
| Publication date | 2022 |
| Pages | 334-336 |
| ISBN (Electronic) | 9781665451765 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | 23rd IEEE International Conference on Mobile Data Management, MDM 2022 - Virtual, Paphos, Cyprus Duration: 6 Jun 2022 → 9 Jun 2022 |
Conference
| Conference | 23rd IEEE International Conference on Mobile Data Management, MDM 2022 |
|---|---|
| Country/Territory | Cyprus |
| City | Virtual, Paphos |
| Period | 06/06/2022 → 09/06/2022 |
| Series | Proceedings - IEEE International Conference on Mobile Data Management |
|---|---|
| Volume | 2022-June |
| ISSN | 1551-6245 |
Bibliographical note
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