International Journal of Research in Engineering and Science (IJRES) ISSN (Online): 2320-9364, ISSN (Print): 2320-9356 www.ijres.org Volume 3 Issue 6 ǁ June 2015 ǁ PP.01-05 www.ijres.org 1 | Page Semantic Search Engine using Ontologies Sumedh Pundkar 1 , Kapil Baheti 2 1(Computer, Usha Mittal Institute of Technology/ SNDT University, India) 2(Computer, Mukesh Patel School of Technology Management and Engineering/NMIMS University, India) ABSTRACT: Nowadays the volume of the information on the Web is increasing dramatically. Facilitating users to get useful information has become more and more important to information retrieval systems. While information retrieval technologies have been improved to some extent, users are not satisfied with the low precision and recall. With the emergence of the Semantic Web, this situation can be remarkably improved if machines could “understand” the content of web pages. The existing information retrieval technologies can be classified mainly into three classes.The traditional information retrieval technologies mostly based on the occurrence of words in documents. It is only limited to string matching. However, these technologies are of no use when a search is based on the meaning of words, rather than onwards themselves.Search engines limited to string matching and link analysis. The most widely used algorithms are the PageRank algorithm and the HITS algorithm. The PageRank algorithm is based on the number of other pages pointing to the Web page and the value of the pages pointing to it. Search engines like Google combine information retrieval techniques with PageRank. In contrast to the PageRank algorithm, the HITS algorithm employs a query dependent ranking technique. In addition to this, the HITS algorithm produces the authority and the hub score. The widespread availability of machine understandable information on the Semantic Web offers which some opportunities to improve traditional search. If machines could “understand” the content of web pages, searches with high precision and recall would be possible. Keywords <ranking, search engine, searching algorithm, semantic search, time rank > I. INTRODUCTION All over the world, people use search engines for some or the other work. Searching the web has become the part of our daily life. This includes everything from searching a food recipe to searching the latest trends in different technologies. Though, searching the internet and user queries have increased but the satisfaction level of the users is still not up to the mark. Users still struggle to get the appropriate information on the internet. Getting the most accurate result for the searched query is a difficult task. Adding to the problem of the user, the number of results returned by the search engine are very large. It is practically impossible to go through all the links and get the answer. The basic problems of the users include: • Displaying the results which are not relevant • Large number of results making difficult for the user to browse • Fetching the results which are not authorized • User is unaware of the logic used to fetch the results for the query making it difficult for user to analyze the results • Low Precision • Low Recall These problems can be observed on any search engine. For example, if the search query is technical related to programming, then the top results are some blogging website. There are several problems with information seeking on the Web. First, the Web is an open system which is constantly changing: new sites appear, old ones change or disappear, and in general the content is always randomly growing rather than planned. This implies that results are not stable and that users may need to vary their strategy over time to satisfy similar needs. Secondly, the quality of information on the Web is extremely variable and the user has to make a judgment. For example, if you submit the query “search engine tutorial” to any of the major search engines you will get many thousands of results. Even if you restrict yourselves to the top 10 ranked tutorials, the ranking provided by the search engine does not necessarily correlate with quality, since the presented tutorials may not have been peer reviewed by experts in a proper manner. Thirdly, factual knowledge on the Web is not objective, so if the query is "who is the president of the United States" result may be several answers. In this case user may trust the White House web site to give a correct answer but other sites may not be so trustworthy. Finally, since the scope of the Web is not fixed, in