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 contributionpeer-review

9 Citations (Scopus)


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
Number of pages15
ISBN (Electronic)9783319261904
ISBN (Print)9783319261898
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)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Web Information Systems Engineering
Abbreviated titleWISE 2015
Country/TerritoryUnited States


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