Selected Papers By topics

Cloud Workflow Scheduling/Temporal Verification:

1. H. Luo, J. Liu, X. Liu, Y. Yang. Predicting Temporal Violations for Parallel Business Cloud Workflow, Software: Practice and Experience. Accepted on Oct. 10, 2017. (ERA A)

2. X. Liu, Y. Yang, D. Yuan and J. Chen, Do We Need to Handle Every Temporal Violation in Scientific Workflow Systems? ACM Transactions on Software Engineering and Methodology, 23(1): Article 5, 2014. (ERA A*)

3. X. Liu, Y. Yang, Y. Jiang and J. Chen, Preventing Temporal Violations in Scientific Workflows: Where and How, IEEE Transactions on Software Engineering, 37(6):805-825, 2011. (ERA A*)

4. X. Liu, Z. Ni, Z. Wu, D. Yuan, J. Chen and Y. Yang, A Novel General Framework for Automatic and Cost-Effective Handling of Recoverable Temporal Violations in Scientific Workflow Systems, Journal of Systems and Software, vol. 84(3):492-509, 2011. (ERA A)

5. X. Liu, Z. Ni, J. Chen, Y. Yang, A Probabilistic Strategy for Temporal Constraint Management in Scientific Workflow Systems, Concurrency and Computation: Practice and Experience, Wiley, 23(16):1893-1919, 2011.(ERA A)

Cloud Data/Service Management

1. D. Yuan, X. Liu and Y. Yang, Dynamic on-the-fly Minimum Cost Benchmarking for Storing Generated Scientific Datasets in the Cloud, IEEE Transactions on Computers, 64(10):2781-2795, 2015. (ERA A*)

2. G. Zhang, X. Liu and Y. Yang, Time-Series Pattern based Effective Noise Generation for Privacy Protection on Cloud. IEEE Transactions on Computers, 64(5):1456-1469, 2015. (ERA A*)

3. D. Yuan, Y. Yang, X. Liu, W. Li, L. Cui, M. Xu and J. Chen, A Highly Practical Approach towards Achieving Minimum Datasets Storage Cost in the Cloud. IEEE Transactions on Parallel and Distributed Systems, 24(6):1234-1244, 2013. (ERA A*)

4. D. Yuan, Y. Yang, X. Liu and J. Chen, On-demand Minimum Cost Benchmarking for Intermediate Datasets Storage in Scientific Cloud Workflow Systems. Journal of Parallel and Distributed Computing, 71(1):316-332, 2011. (ERA A*)

5. D. Yuan, Y. Yang, X. Liu, J. Chen, A Data Placement Strategy in Cloud Scientific Workflows, Future Generation Computer Systems, 26(6): 1200-1214, Elsevier, 2010. (ERA A)

Social Networks and Recommendation

1. Y. Jiang, T. Zhu, X. Liu, Y. Liu, Service Matchmaking for Internet of Things Based on Probabilistic Topic Model, Future Generation Computer Systems, accepted on 26 Nov. 2018. (ERA A)

2. W. Yang, X. Liu, J. Liu, X. Cui, Prediction of Collective Actions Using Deep Neural Network and Species Competition Model on Social Media, World Wide Web, accepted on 26 Nov. 2018. (ERA A)

3. J. Wang, Y. Jiang, Y. Liu, X. Liu, Group Recommendation based on a Bidirectional Tensor Factorization Model, World Wide Web Journal, published online: https://doi.org/10.1007/s11280-017-0493-6, 2017. (ERA A)

4. J. Wang, S. Zhang, X. Liu, Y. Jiang, M. Zhang, A Novel Collective Matrix Factorization Model for Recommendation with Fine-Grained Social Trust Prediction, Concurrency and Computation: Practice and Experience, published online: https://doi.org/10.1002/cpe.4233, 2017. (ERA A)

5. Q. Wang, X. Liu, S. Zhang, Y. Jiang, F. Du, Y. Yue and Y. Liang, A Novel APP Recommendation Method Based on SVD and Social Influence,15^th International Conference on Algorithms and Architectures for Parallel Processing, pp. 269-281, Zhangjiajie, China, November, 2015.

Software Engineering - AI for SE

1. P. Zhou, J. Liu, X. Liu, Z. Yang, J.Grundy, Is Deep Learning Better than Traditional Approaches in Tag Recommendation for Software Information Sites? Information and Software Technology, accepted on 10 Jan. 2019.

2. P. Zhou, J. Liu, Z. Yang, X. Liu, J. Grundy, FastTagRec: Fast Tag Recommendation for Software Information Sites, Automated Software Engineering, published online: http://link.springer.com/article/10.1007/s10515-018-0239-4, June 2018. (ERA A)

3. T. Zheng, X. Zheng, Y. Zhang, Y. Deng, E. Dong, S. Yan, R. Zhang, X. Liu, SmartVM: a SLA-aware Microservice Deployment Framework, World Wide Web, accepted on 4 April 2018. (ERA A)

4. W. Zhang, X. Liu and Y. Yang, Let Smart Ants Help You Reduce the Delay Penalty of Multiple Software Projects, 2017 International Conference on Software Engineering (ICSE Poster Track), Buenos Aires, Argentina, May 20-28, 2017. (ERA A*)

5. D. Du, M. Chen, X. Liu and Y. Yang, A Novel Quantitative Evaluation Approach for Software Project Schedules using Statistical Model Checking, 36th International Conference on Software Engineering, pp. 476-479, Hyderabad, India, June 2014. (ERA A*)

e-Health:

1. S. Ding, H. Huang, Z. Li, X. Liu, S. Yang, SCNET: A Novel UGI Cancer Screening Framework Based on Semantic-Level Multimodal Data Fusion, IEEE Journal of Biomedical and Health Informatics, accepted on 17 March 2020. (ERA A*)

2. J. Pan, S. Ding, S. Yang, G. Li, X. Liu, Endoscopy Report Mining for Intelligent Gastric Cancer Screening, Expert Systems, Accepted on 22 November, 2019.

3. S. Ding, S. Hu, J. Pan, X. Li, G. Li, X. Liu, A homogeneous ensemble method for predicting gastric cancer based on gastroscopy reports, Expert Systems, Accepted on 25 October 2019.

4. W. Li, X. Liu, J. Liu, P. Chen, S. Wan, X. Cui, On Improving the accuracy with Auto-Encoder on Conjunctivitis, Applied Soft Computing, accepted 7 May 2019.

5. X. Li, R. Ding, X. Liu, W. Yan, J. Xu, H. Gao and X. Zheng, COMEC: Computation Offloading for Video-based Heart Rate Detection APP in Mobile Edge Computing, 16th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2018 - Demo Track), accepted on 07 October 2018. Video URL: https://youtu.be/CaEFMbdz0go