Reconsideration of the application of curve segmentation aglorithm in our approach

The curve segmentation algorithm is usually used to approximate a curve in multi-dimension space with a series of lines, including straight lines and arcs. In such a space, the different dimensions are mostly equal in the geometric properties. For example, you can use the same 'ruler' to measure the distance among any two points in this kind of space.

In our project, we exploit the curve segmentation to assist the topic segmentation. We map all entries into an one-dimensional space, and plot them in a two-dimensional plane. However, in the two-dimensional plan we used, each dimension has different meaning. X is for the sequence number of entries and Y for estimated content value. So we must provide a justification of the application of the curve segmentation algorithm to our project.

In fact, when exploiting the curve segmentation algorithm in our project, what I did is just to normalize each dimension into a range [0, 1]. The problem is whether we could directly use the result without any processing. It is really a question!