EMET: Extracting Metadata using ElementTree to Recommend Tags for Web Contents

Web search has become an important task for many individuals. As there is rapid growth of the internet, effective searches plays a vital role. Most of us, however, have tough frustration in making an attempt to search for something on the online. Metadata can be used to facilitate the searching of Web contents. We have proposed an algorithm to extract Metadata using ElementTree [EMET], new search methodology to provide keywords recommendation for Web user contents. The user is guided by an inventory of active keywords that is recommended dynamically throughout the search by a search engine. This active keyword list helps the user to select keywords that are more relevant to the search through recognition. The proposed EMET algorithm yields the average of 0.934 of Precision, 0.927 of Recall and the 0.93 of F-Measure. Keywords— ElementTree, F-Measure, Keyword-based Search, Metadata Extraction, Precision, Query Response, Recall, Tags Recommendation, Search Engine.