Semantic Similarity Based Data Alignment and Best Feature Extraction using PSO for Annotating Search Results from Web Databases
T. Seeniselvi, N. Thangamani · 2014
Due to the development of search engines databases through web reachable all the way through HTML based search boundary in now day’s analysis of data in deep manner from database or web search engines also important to return exact information in search result web pages. In generally the data units received from web accessible search engine databases are frequently prearranged into the result pages energetically for individual browsing. In this paper, consideration of automatic data assignment for SRRs pages returned from original web search engine databases. To conquer these problems proposed an automatic semantic annotation approach through semantic similarity measure for data units and text unit’s results from features for Search results records. The features of data and text units are obtained from Particle Swarm Optimization (PSO) methods. From search results records important feature are extracted and then semantic similarity based measurement are measures are performed to each and every data, text unit nodes. Ontology based system measures semantic similarity between terms in the pages and then aligns the data units in efficient manner. In this work we proficiently analysis the data and most excellent alignment of SRR records. To annotation of new search result from web search engines for various domains in databases we use annotation wrapper. Our experimentation results are estimated based on the parameters like precision and recall for various topics.