DocumentCode :
2579113
Title :
A Hybrid Search Engine Framework for the Internet of Things
Author :
Ding, Zhiming ; Dai, Jian ; Gao, Xu ; Yang, Qi
Author_Institution :
Inst. of Software, Beijing, China
fYear :
2012
fDate :
16-18 Nov. 2012
Firstpage :
57
Lastpage :
60
Abstract :
Efficient retrieval of dynamically generated, spatial-temporal, and heterogeneous sampling data in the Internet of Things is a key challenge in recent years. However, current search engine techniques are not suitable for such kind of data. To solve this problem, we propose a Hybrid Search Engine Technique for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions ("IoT-SVK Search Engine"), in this paper. The IoT-SVK search engine has satisfactory performances in supporting multi-modal retrieval conditions, and thus provides a good solution for real-time searching of massive sampling data in the Internet of Things.
Keywords :
Internet of Things; data handling; information retrieval; search engines; Internet of things; IoT-SVK search engine; hybrid search engine framework; keyword-based conditions; massive sampling data; multimodal retrieval conditions; sampling data; spatial-temporal conditions; value-based conditions; Indexes; Monitoring; Search engines; Servers; Temperature sensors; Trajectory; Internet of Things; Sampling Data; Search Engine; Spatial-Temporal Data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Information Systems and Applications Conference (WISA), 2012 Ninth
Conference_Location :
Haikou
Print_ISBN :
978-1-4673-3054-1
Type :
conf
DOI :
10.1109/WISA.2012.11
Filename :
6385183
Link To Document :
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