Workshop on Knowledge Discovery and Data Mining 

Abstract: This paper deals with the study of a water quality prediction model through application of LS-SVM in Liuxi River in Guangzhou. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value, least squares support vector machine (LS-SVM) combined with particle swarm optimization (PSO) is used to time series prediction. The LS-SVM can overcome some shortcoming in the Multilayer Perceptron (MLP) and the PSO is used to tune the LS-SVM parameters automatically. It enhances the efficiency and the capability of prediction. Through simulation testing the model shows high efficiency in forecasting the water quality of the Liuxi River.

Abstract: This paper proposes a novel technique for detecting faces in color images using AdaBoost algorithm combined with skin color segmentation. First,skin color model in the YCbCr chrominance space is built to segment the non-skin-color pixels from the image. Then, mathematical morphological operators are used to remove noisy regions and fill holes in the skin-color region, so we can extract candidate human face regions. Finally, these face candidates are scanned by cascade classifier based on AdaBoost for more accurate face detection. This system detects human face in different scales, various poses, different expressions, lighting conditions, and orientation. Experimental results show the proposed system obtains competitive results and improves detection performance substantially.

Abstract: Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. Knowledge discovery and data mining can be extremely beneficial for the field of Artificial Intelligence in many areas, such as industry, commerce, government, education and so on. The relation between Knowledge and Data Mining, and Knowledge Discovery in Database (KDD) process are presented in the paper. Data mining theory, Data mining tasks, Data Mining technology and Data Mining challenges are also proposed. This is an belief abstract for an invited talk at the workshop.

Abstract: Network security has been a very important issue, since the rising evolution of the Internet. There has been an increasing need for security systems against the external attacks from the hackers. One important type is the intrusion detection system (IDS). There are two major categories of the analysis techniques of IDS: the anomaly detection and the misuse detection. Here we forcus on misuse detection, the misuse detection collected the attack signatures in a database as the same as virus protection software to detect the relate attacks, we propose an algorithm to use the known signature to find the signature of the related attack quickly.