ECS

a framework for diversified and relevant search in the Internet of Things

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2015
EditorsJianyong Wang, Wojciech Cellary, Dingding Wang, Hua Wang, Shu-Ching Chen, Tao Li, Yanchun Zhang
PublisherSpringer Verlag
Pages448-462
Number of pages15
Volume9418
ISBN (Electronic)9783319261904
ISBN (Print)9783319261898
DOIs
Publication statusPublished - 25 Dec 2015
Externally publishedYes
Event16th International Conference on Web Information Systems Engineering - Miami, United States
Duration: 1 Nov 20153 Nov 2015
Conference number: 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9418
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Web Information Systems Engineering
Abbreviated titleWISE 2015
CountryUnited States
CityMiami
Period1/11/153/11/15

Fingerprint

Internet of Things
Search engines
Search Engine
Thing
Keyword Search
Query
Future Internet
Spectral Clustering
Spectral Methods
Framework
Internet of things
Clustering Methods
Visibility
Paradigm
Attribute
Integrate
Evaluate
Graph in graph theory
Experiment

Cite this

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 J. Wang, W. Cellary, D. Wang, H. Wang, S-C. Chen, T. Li, & Y. Zhang (Eds.), Web Information Systems Engineering – WISE 2015 (Vol. 9418, pp. 448-462). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9418). Springer Verlag. https://doi.org/10.1007/978-3-319-26190-4_30
Shemshadi, Ali ; Yao, Lina ; Qin, Yongrui ; Sheng, Quan Z. ; Zhang, Yihong. / ECS : a framework for diversified and relevant search in the Internet of Things. Web Information Systems Engineering – WISE 2015. editor / Jianyong Wang ; Wojciech Cellary ; Dingding Wang ; Hua Wang ; Shu-Ching Chen ; Tao Li ; Yanchun Zhang. Vol. 9418 Springer Verlag, 2015. pp. 448-462 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Shemshadi, A, Yao, L, Qin, Y, Sheng, QZ & Zhang, Y 2015, ECS: a framework for diversified and relevant search in the Internet of Things. in J Wang, W Cellary, D Wang, H Wang, S-C Chen, T Li & Y Zhang (eds), Web Information Systems Engineering – WISE 2015. vol. 9418, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9418, Springer Verlag, pp. 448-462, 16th International Conference on Web Information Systems Engineering , Miami, United States, 1/11/15. https://doi.org/10.1007/978-3-319-26190-4_30

ECS : a framework for diversified and relevant search in the Internet of Things. / Shemshadi, Ali; Yao, Lina; Qin, Yongrui; Sheng, Quan Z.; Zhang, Yihong.

Web Information Systems Engineering – WISE 2015. ed. / Jianyong Wang; Wojciech Cellary; Dingding Wang; Hua Wang; Shu-Ching Chen; Tao Li; Yanchun Zhang. Vol. 9418 Springer Verlag, 2015. p. 448-462 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9418).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - ECS

T2 - a framework for diversified and relevant search in the Internet of Things

AU - Shemshadi, Ali

AU - Yao, Lina

AU - Qin, Yongrui

AU - Sheng, Quan Z.

AU - Zhang, Yihong

PY - 2015/12/25

Y1 - 2015/12/25

N2 - 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.

AB - 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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M3 - Conference contribution

SN - 9783319261898

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 448

EP - 462

BT - Web Information Systems Engineering – WISE 2015

A2 - Wang, Jianyong

A2 - Cellary, Wojciech

A2 - Wang, Dingding

A2 - Wang, Hua

A2 - Chen, Shu-Ching

A2 - Li, Tao

A2 - Zhang, Yanchun

PB - Springer Verlag

ER -

Shemshadi A, Yao L, Qin Y, Sheng QZ, Zhang Y. ECS: a framework for diversified and relevant search in the Internet of Things. In Wang J, Cellary W, Wang D, Wang H, Chen S-C, Li T, Zhang Y, editors, Web Information Systems Engineering – WISE 2015. Vol. 9418. Springer Verlag. 2015. p. 448-462. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-26190-4_30