Xu Weixiang

A Clustering-Based Approach for Discovering Interesting Places in a Single Trajectory

With the development of many location sensors such as GPS technology and mobile communication devices, a lot of trajectories of users and moving objects can be obtained. These trajectories may contain many interesting individual patterns of the users and moving objects. This creates an appropriate basis for developing efficient new methods for mining moving objects. Semantic clustering of trajectories left behind moving objects is an important aspect in spatio-temporal data mining. Algorithm CB-SMoT (Clustering-Based Stops and Moves of Trajectories) is based on a traditional algorithm DBSCAN which is a classical density-based clustering approach. There is an important parameter Eps in the algorithm CB-SMoT, whose value can dramatically affect the quality of clustering. With in-depth analysis of spatial and temporal characteristics of trajectory data and some related statistical theory, the trajectory data is pre-processed. A new method of calculating the Eps value is proposed. The experiment proves that using this method to calculate the parameter values can significantly improve the quality of clustering.

A New Measurement Method to Calculate Similarity of Moving Object Spatio-Temporal Trajectories by Compact Representation

A new measurement method is proposed to calculate spatio-temporal trajectory similarity, which can reflect the similar degree between two moving object spatio-temporal trajectories compressed by the Maximal Bounding Boxes (MBB). Firstly, the similarity between two trajectories is replaced by the similarity of MBB sequences in respective trajectories which can dramatically decrease the storage volume of the trajectory data. Secondly, some factors affected the similar degree of MBB sequences are analyzed systematically, such as the time duration of overlap between two MBBs in different trajectories, space distance and the density of data points inside the boxes. And then, a similarity measurement formula is proposed by integrating these factors. Experiments show that the proposed measurement formula can improve the value of clustering index Dunn.

Efficiently Using Matrix in Mining Maximum Frequent Itemset

an efficient way to discover the maximum frequent itemset can be very useful for mining association rules, correlations, episodes patterns, etc. Most existing work focuses on the technique for mining candidate maximal frequent itemset and ignores the technique for MFI checking. However the efficient of a MFS mining algorithm lies on these two parts. In this paper, a new MFI checking method is presented based on the optimizing of the former called MaxMatrix and an additional constraint for association rules generating is discussed to save mining time. In order to understand the process of MaxMatrix easily, an example is provided in detail.

Trigonometric polynomial uniform B-spline surface with shape parameter

In this paper, we study in depth a new modeling method of the parameter curve and surface, i.e. uniform trigonometric polynomial B-spline surface with shape parameters. We have designed a series of algorithms. We also develop a Space Freedom Surface Modeling System under Microsoft Visual C++6.0 programmed circumstance, with some examples given as the application of the model. Through experiments, we present the range of change of the shape parameters in this model and discuss its effect on the surface when the controlling polygon remains constant.In this paper, we study in depth a new modeling method of the parameter curve and surface, i.e. uniform trigonometric polynomial B-spline surface with shape parameters. We have designed a series of algorithms. We also develop a Space Freedom Surface Modeling System under Microsoft Visual C++6.0 programmed circumstance, with some examples given as the application of the model. Through experiments, we present the range of change of the shape parameters in this model and discuss its effect on the surface when the controlling polygon remains constant.

Uniform B-Spline Curve and Surface with Shape Parameters

In this paper, we have studied in depth a new modeling method of the parameter curve and surface-uniform b-spline surface with shape parameters. Based on this model, we have given an example of Free-form curve modeling, and analyzed the effect that different shape parameters have on the change of the shape of the curves. In light of the theory of computer graphics, we developed a space free-form surface modeling system (SFSMS) on Microsoft computer. Through the prototype system, we processed with the Free-form surface modeling, gave examples for its application, and discussed how the adjustment of the shape parameters affects the change of the shape of free-form surface.