Mining Complex Concurrency Relationship Patterns for Dynamic Customer/Asset Interaction Modeling through Novel Industrial Behavior Networks

Funding: 2012: $140,000
2013: $120,000
2014: $120,000

Project Member(s): Zhang, C., Cao, L., Chen, L.

Funding or Partner Organisation: Australian Research Council (ARC Linkage Projects)
Coateshire (Coates Hire Pty Ltd)

Start year: 2012

Summary: Understanding customer behaviors and correlations between customers and assets are key factors for success of Business Intelligence (BI) models. With the advancement of communication, network technologies, and the global markets, major businesses are facing the challenges of understanding complex and evolutionary patterns of their customers. This project aims to transform existing tabular-based data-mining BI models to content and behavior interaction based models. As a result, the new BI models can not only consider rich content and interaction information between customers and assets, but also factor in issues, such as season, policy, and events, for supporting faster, more accurate and efficient business decision-making.

Publications:

Han, B, Tsang, IW & Chen, L 1970, 'On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), Springer International Publishing, Riva del Garda, Italy, pp. 665-680.
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Wang, H, Zhang, P, Tsang, I, Chen, L & Zhang, C 1970, 'Defragging Subgraph Features for Graph Classification', Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, CIKM'15: 24th ACM International Conference on Information and Knowledge Management, ACM, Melbourne, VIC, Australia, pp. 1687-1690.
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Yang, W, Gao, Y & Cao, L 2013, 'TRASMIL: A local anomaly detection framework based on trajectory segmentation and multi-instance learning', Computer Vision and Image Understanding, vol. 117, no. 10, pp. 1273-1286.
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Liu, B, Xiao, Y, Yu, PS, Cao, L & Hao, Z 1970, 'Robust Textual Data Streams Mining Based on Continuous Transfer Learning', Proceedings of the 2013 SIAM International Conference on Data Mining, Proceedings of the 2013 SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, Austin, Texas, USA, pp. 731-739.
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Liu, C, Chen, L & Zhang, C 1970, 'Mining Probabilistic Representative Frequent Patterns From Uncertain Data', Proceedings of the 2013 SIAM International Conference on Data Mining, Proceedings of the 2013 SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, Austin, Texas, USA, pp. 73-81.
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Liu, C, Chen, L & Zhang, C 1970, 'Summarizing probabilistic frequent patterns', Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, Chicago, Illinois USA, pp. 527-535.
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Wan, L, Chen, L & Zhang, C 1970, 'Mining Dependent Frequent Serial Episodes from Uncertain Sequence Data', 2013 IEEE 13th International Conference on Data Mining, 2013 IEEE International Conference on Data Mining (ICDM), IEEE, Dallas, TX, USA, pp. 1211-1216.
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Long, G, Chen, L, Zhu, X & Zhang, C 1970, 'TCSST', Proceedings of the 21st ACM international conference on Information and knowledge management, CIKM'12: 21st ACM International Conference on Information and Knowledge Management, ACM, Maui, Hawaii, USA, pp. 764-772.
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Keywords: data mining and machine learning;business intelligence;behavior modeling and interaction analysis

FOR Codes: Pattern Recognition and Data Mining, Application Software Packages (excl. Computer Games), Business Information Management (incl. Records, Knowledge and Information Management, and Intelligence), Property, Business Support Services and Trade not elsewhere classified, Information Processing Services (incl. Data Entry and Capture), Data mining and knowledge discovery, Business information management (incl. records, knowledge and intelligence), Property, business support services and trade not elsewhere classified, Application software packages, Information systems, technologies and services not elsewhere classified

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.