Research Issues for Web Structural Delta Mining

Web structure mining has been a well-researched area during recent years. However, we observed that data on the web is changing at any time in any way, even though there are some incremental data mining algorithms that are proposed to update the mining results with the corresponding changes, none of the existing web structure mining techniques is able to extract useful and hidden knowledge from the sequence of historical web structural changes. In this paper, we proposed a novel research area of web structure mining named web structural delta mining. The distinct feature of our research is that our mining object is the sequence of historical changes of web structure (Web Structural Deltas). For web structural delta mining, we aim to extract useful, interesting, and novel web structures and knowledge considering their historical, dynamic, and temporal properties. We proposed three major issues of web structural delta mining, identify useful and interesting structures, extract association from changes of web structure, and cluster web structure based on patterns of changes. Also, the challenges of web structural delta mining corresponding to different issues are discussed in this