A metaheuristic approach wrapper generation for web data alignment and Annotation from web databases

Abstract

Today World Wide Web (WWW) is the major all kind of information store and has been very successful in providing information to individuals. The web has become the ideal medium for several database applications and these applications stores data in large databases that user s query, access and update via the web. The web databases return several search results dynamically on the web browser, these search results contains deep web pages in the Hyper Text Markup Language (HTML) page format. Every web page comprises multiple Search Result Records (SRR) related to the query. These search results have to be extracted and meaningful labels have to be assigned. In this research work, automatic annotation approach has been presented that aligns the data units on the result page into various groups, each group contains data having the same semantic. Each group is then annotated from various aspects and these annotations are aggregated to predict the final annotation. Then, annotation wrapper is automatically constructed for the search site and is utilized to annotate new results from the same web databases. In this research an unsupervised learning methodology is applied to generate wrappers for the web page. newline In this work, proposed BAT algorithm, is an optimization algorithm based on the echolocation behavior of bats. The capability of echolocation of bats is fascinating as these bats can find their prey and discriminate different types of insects even in complete darkness. The advanced capability of echolocation of bats has been used to solve different optimization problems. Results show that the proposed technique with SOFM and BAT optimization achieved better performance by precision and recall when compared with proposed technique with DOM alignment and BAT optimization. newline newline