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Trust-aware internet of things service recommendation

Funding: 2018: $122,751
2019: $122,718
2020: $122,977
2019: $16,720
2020: $122,964
2021: $124,966
2022: $109,456

Project Member(s): Wang, X.

Funding or Partner Organisation: Australian Research Council (ARC DECRA Scheme)
Australian Research Council (ARC DECRA Scheme)

Start year: 2019

Summary: This project centres on the emerging Internet of Things, the number one technology that is expected to reshape the world and human society in the coming decades. It aims to develop innovative techniques and tools to recommend Internet of Things resources as services for trustworthy and cost-effective applications. This project will output novel techniques for the trust-aware recommendation of Internet of Things resources by modelling, evaluating, and relating Internet of Things data. The research will underpin innovative applications like smart home, urban computing, and mobile social sensing, which can significantly contribute to Australian society and the national economy. It also holds the potential to place Australia at the forefront of research and development in the vibrant and growing area of trustworthy Internet of Things.

Publications:

Chen, K, Yao, L, Zhang, D, Wang, X, Chang, X & Nie, F 2020, 'A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition.', IEEE Transactions on Neural Networks and Learning Systems.
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Huang, C, Yao, L, Wang, X, Benatallah, B & Sheng, QZ 2020, 'Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network', Pattern Recognition Letters, vol. 130, pp. 46-53.
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Xiao, Y, Pei, Q, Yao, L, Yu, S, Bai, L & Wang, X 2020, 'An enhanced probabilistic fairness-aware group recommendation by incorporating social activeness', JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, vol. 156.
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Altulyan, M, Yao, L, Kanhere, SS, Wang, X & Huang, C 2019, 'A unified framework for data integrity protection in people-centric smart cities', Multimedia Tools and Applications.
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CHEN, J, SU, S & WANG, X 2019, 'Towards Privacy-Preserving Location Sharing over Mobile Online Social Networks', IEICE TRANSACTIONS on Information and Systems, vol. 102, pp. 133-146.
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Li, M, Sun, Y, Su, S, Tian, Z, Wang, Y & Wang, X 2019, 'DPIF: A framework for distinguishing unintentional quality problems from potential shilling attacks', Computers, Materials and Continua, vol. 59, no. 1, pp. 331-344.
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Sun, Y, Tian, Z, Wang, Y, Li, M, Su, S, Wang, X & Fan, D 2019, 'Lightweight Anonymous Geometric Routing for Internet of Things', IEEE ACCESS, vol. 7, pp. 29754-29762.
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Wang, Y, Sun, Y, Su, S, Tian, Z, Li, M, Qiu, J & Wang, X 2019, 'Location privacy in device-dependent location-based services: Challenges and solution', Computers, Materials and Continua, vol. 59, no. 3, pp. 983-993.
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Yao, L, Wang, X, Sheng, QZ, Dustdar, S & Zhang, S 2019, 'Recommendations on the Internet of Things: Requirements, Challenges, and Directions', IEEE Internet Computing, vol. 23, no. 3, pp. 46-54.
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Bai, L, Yao, L, Kanhere, SS, Wang, X & Sheng, QZ 2019, 'StG2seq: Spatial-temporal graph to sequence model for multi-step passenger demand forecasting', IJCAI International Joint Conference on Artificial Intelligence, pp. 1981-1987.
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Bai, L, Yao, L, Kanhere, SS, Wang, X & Yang, Z 2018, 'Automatic Device Classification from Network Traffic Streams of Internet of Things', 2018 IEEE 43rd Conference on Local Computer Networks (LCN 2018), IEEE Conference on Local Computer Networks, IEEE, USA, pp. 597-605.
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Bai, L, Yao, L, Kanhere, SS, Wang, X, Liu, W & Yang, Z 2019, 'Spatio-temporal graph convolutional and recurrent networks for citywide passenger demand prediction', International Conference on Information and Knowledge Management, Proceedings, ACM International Conference on Information and Knowledge Management, ACM, Beijing, China, pp. 2293-2296.
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Bai, L, Yao, L, Kanhere, SS, Yang, Z, Chu, J & Wang, X 2019, 'Passenger demand forecasting with multi-task convolutional recurrent neural networks', Advances in Knowledge Discovery and Data Mining (LNAI), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, Macau, China, pp. 29-42.
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Dong, M, Yao, L, Wang, X, Benatallah, B & Huang, C 2019, 'Similarity-aware deep attentive model for clickbait detection', Advances in Knowledge Discovery and Data Mining (LNAI), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, Macau, China, pp. 56-69.
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Dong, M, Yao, L, Wang, X, Benatallahl, B, Zhang, X & Sheng, QZ 2019, 'Dual-stream Self-Attentive Random Forest for False Information Detection', 2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), International Joint Conference on Neural Networks (IJCNN), IEEE, Budapest, HUNGARY.

FOR Codes: Interorganisational Information Systems and Web Services, Database Management, Application Software Packages (excl. Computer Games), Electronic Information Storage and Retrieval Services