Research
Research Interests
Sentiment Analysis Question Answering Systems Automated Reasoning Semantic Web
Research Projects
Introducing Conditional Proof into Logic Programming This project investigates the possibility of introducing conditional proof which is an important proof technique of deductive logic into logic programming. It analyses the necessity and feasibility, and formulises the procedure. Incorporating conditional proof into SLD-resolution (or GOPT-resolution) increases the power of the derivation. Hence problems which cannot be solved by SLD-resolution (or GOPT-resolution) can, now, be solved by the variation of SLD-resolution (or GOPT-resolution). Approximate Reasoning in PT-Resolution This project studies the feasibility of integrating approximate reasoning into PT-resolution. PT-resolution is a deduction method based on partial intersection and truncation. The integration enables the deduction to handle quantitative data in an approximate manner. Object Oriented Web Information Specification With the fast expansion of the World Wide Web and rapid advances in Information Technology, there is a great demand for an intelligent search engine -- the search engine not only can conduct pattern marching, but also can deduce (ie. to derive information from existing information). This requires an effective mechanism in information representation, retrieval and derivation. In this project, we investigate the feasibility of extending an object oriented language for web information representation and derivation. The extension can be made on an existing language. The significance of the research is that it enables us to build a powerful tool for web information representation and derivation based on the existing infrastructure.
Recent Publications
2014
[1]	Youseef A. and Liu F. (2013), A Novel Secure Business Process Modeling and its Impacts on Business Performance, Information Sciences, (accepted).
[2]	Youseef A. and Liu F. (2013), An Empirical Study of a Novel Managing Customer Power Model and Business Performance in the Mobile Service Industry, Business Process Management Journal (accepted).
[3]	Li, G. and Liu F., Sentiment analysis based on clustering: a framework in improving accuracy and recognizing neutral opinions, Applied Intelligence, (full text).
2013
[4]	Tengku Izhar, T. A., Torabi, T. Bhatti M. I. and Liu F., (2013) Recent Developments in the Organization Goals Conformance Using Ontology, Expert Systems with Applications, Volume 30 Issue 10, pp. 4252-4267.
[5]	Youseef A. and Liu F. (2013) Average waiting time of customers in a new queue system with different classes, Business Process Management Journal, Volume 19 Issue 1, pp.146 – 168. (full text)
2012
[6]	Li, G. and Liu, F. (2012) Application of a Clustering Method on Sentiment Analysis, Journal of Information Science, Volume 38, Issue 2, April 2012, pp.127–139.
[7]	Alotaibi, Y. and Liu F. (2012) A Novel Framework to Model a Secure Information System (IS), Proceedings of 2012 International Conference on Information and Computer Applications (ICICA 2012), pp. 84 - 89. (The paper was awarded the best paper by the conference and it was selected to be published by International Journal of Information and Education Technology (IJIET)).
[8]	Al-Sudani, W., Gill, A., Li, C., Wang, J. and Liu, F. (2012) Protection through Intelligent and Multimedia CAPTCHAs, International Journal of Adaptive, Resilient and Autonomic System, Volume 3, Issue 2, April-June 2012, pp. 44 – 58.
[9]	Alotaibi, Y. and Liu, F. (2012) Business Process Modelling Towards Derivation of Information Technology Goals, proceedings of 45th Hawaii International Conference on System, pp. 4307– 4315.
[10]	Alotaibi, Y. and Liu, F. (2012) How to Model a Secure Information System (IS): A Case Study, International Journal of Information and Education Technology, Volume 2, No. 2, pp. 94 -102.
[11]	Alotaibi, Y. and Liu, F. (2012) A New Framework to Model a Secure E-Commerce System, International Journal of Social and Human Sciences, Volume 6, pp. 162 – 168.
[12]	Wang, T., Guan, S.U., Ting, T.O., Man, K.L. and Liu, F., Evolving Linear Discriminant in a Continuously Growing Dimensional Space for Incremental Attribute Learning, Proceedings of The 9th IFIP International Conference on Network and Parallel Computing, LNCS 7513, pp. 487–496.
[13]	Do, M., Loke, S. and Liu, F., ASR: ASP-based Stream Reasoning for Activity Recognition, proceedings of 9th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, to be published in December 2012.
[14]	Wang, T., Guan S.U. and Liu, F. (2012) Correlation-based Feature Ordering for Classification based on Neural Incremental Attribute Learning, International Journal of Machine Learning and Computing, Volume 2, Number 6, pp. 807-811.
[15]	Wang, T., Guan S.U. and Liu, F., Entropic feature discrimination ability for pattern classification based on neural IAL, Proceedings of 9th International Symposium on Neural Networks, ISNN 2012. LNCS 7368, pp.30-35.
2011
[16]	Liu, F. and Roddick, J., GOPT Resolution, International Journal of Artificial Intelligence and Soft Computing, Volume 2, Number 4, 2011, pp. 334 – 352.
[17]	Xie J., Liu F. and Guan S., Tree-Structure Based Ontology Integration, Journal of Information Science, Volume 37, Issue 6, December 2011, pp. 594 – 613.
[18]	Do, T.M., Loke, S.W., and Liu, F., Answer Set Programming for Stream Reasoning, 24th Canadian Conference on Artificial Intelligence (2011) LNAI 6657, pp.104 – 109.
[19]	Ting Wang, Sheng-Uei Guan, Fei Liu^,Feature Discriminability for Pattern Classification Based on Neural Incremental Attribute Learning, Proceedings of 2011 International Conference on Intelligent Systems and Knowledge Engineering (2011), pp. 275 – 280.
2010
[20]	Li G. and Liu F., A Clustering-Based Approach on Sentiment Analysis, Proceedings of IEEE International Conference on Intelligent System and Knowledge Engineering, November 2010, pp. 331-337.
[21]	Xie J. and Liu F., A Framework on Ontology Integration, Proceedings of 12^th International Conference on Information Integration and Web-based Applications & Services, November 2010, pp.663 – 667.
[22]	Al-Sudani W., Gill A., Li C., Wang J. and Liu F., Protection Through Multimedia CAPTCHAS, Proceedings of The 8th International Conference on Advances in Mobile Computing & Multimedia, November 2010. pp. 63 – 68.
2009
[23]	Vølstad T., Liu F. and Guan S-U., Layered RDF - An Object-Oriented Approach to Web Information Representation, Web Intelligence and Agent Systems: An International Journal, Volume 7, Number 3, 2009, pp. 281 – 301.
[24]	Le V. H., Liu F. and Tran D. K., Fuzzy Linguistic Logic Programming and Its Applications, Theory and Practice of Logic Programming, Volume 9, Issue 3, 2009, pp.309-341.
[25]	Le V, Liu F. and Lu H., An Data Model for Fuzzy Linguistic Databases with Flexible Querying, Proceedings of The 22^nd Australasian Joint Conference in Artificial Intelligence, 2009, Lecture Notes in Artificial Intelligence (LNAI 5866), pp. 493 – 505.