Development of Cluster based Supervised Learning Technique for Web News Extraction

World Wide Web makes it a prominent source of online information as abundance of data is available on the web and lots of data gets uploaded on daily basis. Due to the presence of massive information on the web it seems easier and simpler to get any information at any time effortlessly, but it requires a lot of focus. Numerous web mining techniques have been studied like extractors, wrappers etc, that provide various methods to extract useful web content. In this paper a semisupervised web news extraction technique is proposed that uses unsupervised clustering technique and supervised classification technique.