Multidimensional Database Model for Web Content Mining
Vikrant Sabnis, R. S. Thakur · CiiT international journal of data mining and knowledge engineering · 2013
With increase in network technologies and number of users working on the network, attempts are being made to discover the useful knowledge from the secondary data. For retrieving knowledge large number of models, techniques and methods are evolving continuously in the area of web content mining. These techniques are becoming very critical for effective management of web sites in the variety of domains such as business, education and e-learning. Based on the prediction approach the user browsing behaviors can be guessed and this information can be utilized for building of proper web sites. This paper proposes star schema for web contents mining from the complex data which is multidimensional in nature. Further the association among web contents is explored using multidimensional ARM approach to know the surfing behavior of web users. At the end Performance computation of proposed work has been discussed, which shows improvement in the gain and implementation explains well the significance of multidimensional association rule in web content data. The paper also compares pros and cons with the traditional state of art approaches.