文章基本信息

标题：Relevant Pages in semantic Web Search Engines using Ontology
本地全文：下载
作者：Jemimah Simon ; K. Raja ; Dr. G. Tholkappia Arasu 等
期刊名称：International Journal of Electronics and Computer Science Engineering
电子版ISSN：2277-1956
出版年度：2012
卷号：1
期号：2
页码：578-584
出版社：Buldanshahr : IJECSE
摘要：In general, search engines are the most popular means of searching any kind of information from the Internet. Generally, keywords are given to the search engine and the Web database returns the documents containing specified keywords. In many situations, irrelevant results are given as results to the user query since different keywords are used in different forms in various documents. The development of the next generation Web, Semantic Web, will change this situation. This paper proposes a prototype of relation-based search engine which ranks the page according to the user query and on annotated results. Page sub graph is computed for each annotated page in the result set by generating all possible combinations for the relation in the sub graph. A relevance score is computed for each annotated page using a probability measure. A relation based ranking model is used which displays the pages in the final result set according to their relevance score. This ranking is provided by considering keyword-concept associations. Thus, the final result set contains pages in the order of their constrained relevant scores
关键词：Semantic Web; Ontology; Ranking.