Adapted Clustering Based on Maximal Spanning Tree in Collaborative Editing Systems

Collaborative applications across mobile end and immobile end became more and more popular recently; however, the control over user interface became more intricate or flexible. The clustering of editing objects could give users not only a clear document organization, but also a smart management of operation authority. In this paper we presents an adapted clustering algorithm based on maximal spanning tree that could adjust user power and interface dynamically. The algorithm reduced the load of designer and promoted the upgrade of system. It had been tested in our prototype and proved to be valuable for the application development in heterogeneous collaborative editing systems.