Modeling Inconsistent Data for Reasoners in Web of Things

BLANCO SÁNCHEZ, José Miguel, Mouzhi GE a Tomáš PITNER. Modeling Inconsistent Data for Reasoners in Web of Things. Online. In Procedia Computer Science, Volume 192, 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021. Szczecin: Elsevier, 2021, s. 1265-1273. ISSN 1877-0509. Dostupné z: https://dx.doi.org/10.1016/j.procs.2021.08.130.

Základní údaje

• Originální název: Modeling Inconsistent Data for Reasoners in Web of Things
• Autoři: BLANCO SÁNCHEZ, José Miguel (724 Španělsko, garant, domácí), Mouzhi GE (156 Čína) a Tomáš PITNER (203 Česká republika, domácí).
• Vydání: Szczecin, Procedia Computer Science, Volume 192, 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021, od s. 1265-1273, 9 s. 2021.
• Nakladatel: Elsevier

Další údaje

• Originální jazyk: angličtina
• Typ výsledku: Stať ve sborníku
• Obor: 10201 Computer sciences, information science, bioinformatics
• Stát vydavatele: Nizozemské království
• Utajení: není předmětem státního či obchodního tajemství
• Forma vydání: elektronická verze "online"
• Kód RIV: RIV/00216224:14330/21:00122772
• Organizační jednotka: Fakulta informatiky
• ISSN: 1877-0509
• Doi: http://dx.doi.org/10.1016/j.procs.2021.08.130
• UT WoS: 000720289001032
• Klíčová slova anglicky: Web of Things Internet of Things Semantic Web Reasoners
• Štítky: firank_B

Anotace

With the recent developments of the Internet of Things and its integration in the web environment, the Web of Things and the real-time data submissions to Reasoners are enabled. However, the data that are fed to the Reasoners are often inconsistent. This can be possibly caused by the malfunction of certain Internet of Things device or by human errors. The data consistency issue is becoming more complex in the Web of Things network. This paper, therefore, proposes a new data processing model to tackle the inconsistent data, so that the processed data can be further used in Reasoners. The data processing model introduces an oversimplification of the Shramko-Wansing sixteen-valued trilattice, which is an extension of Belnap’s four-valued bilattice to assign the data classical truth-values. A preliminary implementation is demonstrated to validate the proposed model. The result shows that our model can avoid system collapse when contradictory outputs exist.