Extraction of Knowledge from Online Databases

Web is to create metadata by mass collaboration by grouping related content created by the group of people. Extracting the data from the web that means online database by using annotating. Databases are web accessible through HTML form based interface. When query is given to the search engine knowledge can be extracted. Results pages returned from the Online Databases. An online database has multiple search result records. Semantic labels of the data units are not presented in result pages. Having semantic labels for data units is not only important for the above record linkage task, but also for storing collected SRRs into a database table. Early applications require human efforts to annotate data units manually. This is having limit scalability. In this paper, we consider how to automatically assign labels to the data units within the SRRs returned from WDBs improve the results by using clustering methods that is BIRCH and ROCK. First aligns the data units on a result page into different groups such that the data in the same group having same semantics. By using Annotation wrapper knowledge can be extracted from the web databases. Our experiment indicates that the proposed approach is highly effective.