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http://dx.doi.org/10.3837/tiis.2022.05.005

Keywords and Spatial Based Indexing for Searching the Things on Web  

Faheem, Muhammad R. (School of Systems and Technology, University of Management and Technology)
Anees, Tayyaba (School of Systems and Technology, University of Management and Technology)
Hussain, Muzammil (School of Systems and Technology, University of Management and Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.16, no.5, 2022 , pp. 1489-1515 More about this Journal
Abstract
The number of interconnected real-world devices such as sensors, actuators, and physical devices has increased with the advancement of technology. Due to this advancement, users face difficulties searching for the location of these devices, and the central issue is the findability of Things. In the WoT environment, keyword-based and geospatial searching approaches are used to locate these devices anywhere and on the web interface. A few static methods of indexing and ranking are discussed in the literature, but they are not suitable for finding devices dynamically. The authors have proposed a mechanism for dynamic and efficient searching of the devices in this paper. Indexing and ranking approaches can improve dynamic searching in different ways. The present paper has focused on indexing for improving dynamic searching and has indexed the Things Description in Solr. This paper presents the Things Description according to the model of W3C JSON-LD along with the open-access APIs. Search efficiency can be analyzed with query response timings, and the accuracy of response timings is critical for search results. Therefore, in this paper, the authors have evaluated their approach by analyzing the search query response timings and the accuracy of their search results. This study utilized different indexing approaches such as key-words-based, spatial, and hybrid. Results indicate that response time and accuracy are better with the hybrid approach than with keyword-based and spatial indexing approaches.
Keywords
API; Geo-spatial; Indexing; JSON; JSON-LD; Schema; sensor Things; Solr; Things;
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