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Lee, GM, Hussein, D, Han, SN and Crespi, N (2015) Social Cloud-based Cognitive Reasoning for Task-oriented Recommendation. IEEE Cloud Computing, 2 (6). pp. 10-19. ISSN 2325-6095
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Abstract
The Social Internet of Things (SIoT) is recently being promoted in literature for enabling the integration of devices into users’ daily life. This integration can be achieved by taking advantage of the inter-connectivity and the user-friendliness offered by Social Network Services (SNS). The novel SIoT paradigm opens the door for studying the intelligence mechanisms required to enhance services adaptability. We study the integration of cognitive reasoning into SIoT for providing recommendation of quotidian tasks in smart homes. In order to achieve situation characterization, reasoning about physical as well as social aspects of context is required. Thus, as a service built on top of Social Cloud (SoC), we propose an intelligent recommendation (InRe) framework. This framework applies the reasoning mechanism on context elements which are represented using ontologies. ThigsChat is provided as a proof-of-concept prototype. Initial experiments indicate a considerable improvement in adaptability of recommendation results to users’ situations.
| Item Type: | Article |
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| Additional Information: | (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works |
| Uncontrolled Keywords: | Social Internet of Things; Social Network services; context-awareness; Social Cloud |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computer Science and Mathematics |
| Publisher: | IEEE |
| Date Deposited: | 19 Nov 2015 13:05 |
| Last Modified: | 04 Sep 2021 13:47 |
| DOI or ID number: | 10.1109/MCC.2015.117 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/2365 |
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