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Annotating Search Results from Web Databases Using Clustering-Based Shifting

Saranya.J, SelvaKumar.M, Vigneshwaran.S, Danessh.M.S

An increasing number of databases have become web accessible through HTML formbased search interfaces. The data units returned from the underlying database are usually encoded into the result pages dynamically for human browsing. For the encoded data units to be machine processable, which is essential for many applications such as deep web data collection and Internet comparison shopping, they need to be extracted out and assigned meaningful labels. In this paper, we present an automatic annotation approach that first aligns the data units on a result page into different groups such that the data in the same group have the same semantic. Then, for each group we annotate it from different aspects and aggregate the different annotations to predict a final annotation label for it. An annotation wrapper for the search site is automatically constructed and can be used to annotate new result pages from the same web database. Our experiments indicate that the proposed approach is highly effective. So this paper uses data alignment, data annotation, web databases and wrapper generation as the term to provide the user with much better result while they search for the terms.