Xiaoshu Hang

According to our database1, Xiaoshu Hang authored at least 12 papers between 2001 and 2005.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2005
An Incremental FP-Growth Web Content Mining and Its Application in Preference Identification.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2005

Applying both positive and negative selection to supervised learning for anomaly detection.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005

A Novel Field Learning Algorithm for Dual Imbalance Text Classification.
Proceedings of the Fuzzy Systems and Knowledge Discovery, Second International Conference, 2005

2004
An Immune Network Approach for Web Document Clustering.
Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2004), 2004

Combining Extension Matrix and Integer Programming for Optimal Concept Learning.
Proceedings of the PRICAI 2004: Trends in Artificial Intelligence, 2004

An Extended Negative Selection Algorithm for Anomaly Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2004

Constructing Detectors in Schema Complementary Space for Anomaly Detection.
Proceedings of the Genetic and Evolutionary Computation, 2004

2003
A Web content based data mining for car consumption preference in China.
Proceedings of the 2003 IEEE International Conference on Information Reuse and Integration, 2003

An Incremental FP-Growth Approach for Web-Content Based Dynamic Data Mining.
Proceedings of the International Conference on Artificial Intelligence, 2003

Mining Sequential Causal Patterns with User-Specified Skeletons in Multi-Sequence of Event Data.
Proceedings of the Design and Application of Hybrid Intelligent Systems, 2003

An Optimal Strategy for Extracting Probabilistic Rules by Combining Rough Sets and Genetic Algorithm.
Proceedings of the Discovery Science, 6th International Conference, 2003

2001
Inexact Field Learning: An Approach to Induce High Quality Rules from Low Quality Data.
Proceedings of the 2001 IEEE International Conference on Data Mining, 29 November, 2001


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