Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/108664
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Conference paper |
Title: | ThingsNavi: finding most-related things via multi-dimensional modeling of human-thing interactions |
Author: | Yao, L. Sheng, Q. Falkner, N. Ngu, A. |
Citation: | Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2014, pp.20-29 |
Publisher: | ICST |
Publisher Place: | online |
Issue Date: | 2014 |
ISBN: | 9781631900396 |
Conference Name: | 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) (2 Dec 2014 - 5 Dec 2014 : London, UK) |
Statement of Responsibility: | Lina Yao, Quan Z. Sheng, Nickolas Falkner, Anne Ngu |
Abstract: | With the fast emerging Internet of Things (IoT), effectively and efficiently searching and selecting the most related things of a user’s interest is becoming a crucial challenge. In the IoT era, human interactions with things are taking place at a new level in ubiquitous computing. These interactions initiated by humans are not completely random and carry rich contextual information. In this paper, we propose a things searching approach based on a hypergraph, called ThingsNavi, where given a target thing, other related things can be found by fully exploiting human-thing interactions in terms of multi-dimensional, contextual information (e.g., spatial information, temporal information, user identity). In particular, we construct a unified hypergraph to represent the rich structural and contextual information in human-thing interactions. We formulate the correlated things search as a ranking problem on top of this hypergraph, in which the information of target things can be propagated through the structure of the hypergraph. We evaluate our approach by using real-world datasets and the experimental results demonstrate its effectiveness. |
Keywords: | Internet of Things, things discovery; hypergraph; ranking |
Rights: | Copyright © 2014 |
DOI: | 10.4108/icst.mobiquitous.2014.258007 |
Published version: | https://dl.acm.org/citation.cfm?id=2692987 |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
RA_hdl_108664.pdf Restricted Access | Restricted Access | 794.13 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.