SABC-SBC: a hybrid ontology based image and webpage retrieval for datasets

Abstract

In the recent days, web mining is the one of the most widely used research area for finding the patterns from the web page. Similarly, web content mining is defined as the process of extracting some useful information from the web pages. For this mining, a Block Acquiring Page Segmentation (BAPS) technique is proposed in the existing work, which removes the irrelevant information by retrieving the contents. Also, the Tag-Annotation-Demand (TAD) re-ranking methodology is employed to generate the personalized images. The major disadvantage of these techniques is that it fails to retrieve both the images and web page contents. In order to overcome this issue, this paper focused to integrate the TAD and BAPS techniques for the image and web page content retrieval. There are two important steps are involved in this paper, which includes, server database upload and content extraction from the database. Furthermore, the databases are applied on the Semantic Annotation Based Clustering (SABC) for image and Semantic Based Clustering (SBC) for webpage content. The main intention of the proposed work is to accurately retrieve both the images and web pages. In experiments, the performance of the proposed SABC technique is evaluated and analyzed in terms of computation time, precision and recall.