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ECS: A Framework for Diversified and Relevant Search in the Internet of Things

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Web Information Systems Engineering – WISE 2015 (WISE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9418))

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Abstract

Things search engines play a key role in increasing the visibility of the emerging Internet of Things (IoT) paradigm. Developing an innovative search approach is a fundamental step to lay the foundations of future IoT search engines. Currently, the most adopted approach for searching things is based on keyword search. Unfortunately, keyword search does not provide enough functionality for an IoT search engine. Correlating things based on their attributes is an emerging approach which can potentially improve the IoT search process. Since in reality there might exist a number of different correlations between a pair of everyday objects, integrating and applying them in IoT search is challenging. In this paper, we propose the ECS (Extract, Cluster, Select) framework. Our framework contains a novel approach to extract and integrate different types of correlation graphs with a spectral clustering method and a selection method to improve the coherence and the diversity of top-k results for a given search query. We evaluate our framework through extensive experiments using real-world datasets from different domains of IoT applications. The results show that the quality of search results improves greatly after we diversify the results of IoT data queries.

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Notes

  1. 1.

    http://cran.r-project.org/web/packages/ggmap/index.html.

  2. 2.

    http://thingful.net.

  3. 3.

    http://wiki.knoesis.org/index.php/SSW_Datasets.

  4. 4.

    http://mesowest.utah.edu/index.html.

  5. 5.

    http://www.geonames.org/.

  6. 6.

    http://www.opengeospatial.org/standards/sensorml.

  7. 7.

    http://www.w3.org/2005/Incubator/ssn/ssnx/ssn.

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Authors and Affiliations

  1. School of Computer Science, The University of Adelaide, Adelaide, SA, 5005, Australia

    Ali Shemshadi, Lina Yao, Yongrui Qin, Quan Z. Sheng & Yihong Zhang

Authors
  1. Ali Shemshadi
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  2. Lina Yao
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  3. Yongrui Qin
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  4. Quan Z. Sheng
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  5. Yihong Zhang
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Corresponding author

Correspondence to Ali Shemshadi .

Editor information

Editors and Affiliations

  1. Tsinghua University, Bijing, China

    Jianyong Wang

  2. Poznan University of Economics, Poznan, Poland

    Wojciech Cellary

  3. Florida Atlantic University, Boca Raton, Florida, USA

    Dingding Wang

  4. Victoria University, Melbourne, Australia

    Hua Wang

  5. School of Computing & Information, Florida International University, Miami, Florida, USA

    Shu-Ching Chen

  6. Florida International University, Miami, Florida, USA

    Tao Li

  7. Victoria University, Melbourne, Victoria, Australia

    Yanchun Zhang

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© 2015 Springer International Publishing Switzerland

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Shemshadi, A., Yao, L., Qin, Y., Sheng, Q.Z., Zhang, Y. (2015). ECS: A Framework for Diversified and Relevant Search in the Internet of Things. In: Wang, J., et al. Web Information Systems Engineering – WISE 2015. WISE 2015. Lecture Notes in Computer Science(), vol 9418. Springer, Cham. https://doi.org/10.1007/978-3-319-26190-4_30

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  • DOI: https://doi.org/10.1007/978-3-319-26190-4_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26189-8

  • Online ISBN: 978-3-319-26190-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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