Intelligent Semantic Web Search Engines: A Brief Survey <s> INTRODUCTION <s> From the Publisher: ::: As the World Wide Web continues to expand, it becomes increasingly difficult for users to obtain information efficiently. Because most search engines read format languages such as HTML or SGML, search results reflect formatting tags more than actual page content, which is expressed in natural language. Spinning the Semantic Web describes an exciting new type of hierarchy and standardization that will replace the current "web of links" with a "web of meaning." Using a flexible set of languages and tools, the Semantic Web will make all available information--display elements, metadata, services, images, and especially content--accessible. The result will be an immense repository of information accessible for a wide range of new applications. ::: This first handbook for the Semantic Web covers, among other topics, software agents that can negotiate and collect information, markup languages that can tag many more types of information in a document, and knowledge systems that enable machines to read Web pages and determine their reliability. The truly interdisciplinary Semantic Web combines aspects of artificial intelligence, markup languages, natural language processing, information retrieval, knowledge representation, intelligent agents, and databases. <s> BIB001 </s> Intelligent Semantic Web Search Engines: A Brief Survey <s> INTRODUCTION <s> With the growth of the web, information explosion has taken place in the form of "Big Bang”. A well-support semantic based search engine needs to display the few specific pages from the billons available in which users have interest. Therefore, search engines have become one of the most important and helpful tools for obtaining information from the Internet. But most of the search engines are suffering from drawbacks of human and time consumption. Instead of caring about the exact meaning of semantics of information, the machines on the current web are caring about the location and display of information only. Because of this shortcoming of the current web, the search results produced by even most popular search engines are not satisfactory. Search engine activities in current web are not particularly well supported by software tools except for keyword-based search and suffer from lack of semantics and as well as semantic based search engine also lack of knowledge of semantics like RDF, Ontology, Query language like SQL. This paper presents an analysis of the role of search engines in intelligent web and to present a theoretical model to explore some method and possibilities for intelligent and meaningful retrieval of information on web for the ordinary users who are not the aware of semantic knowledge. <s> BIB002
The Semantic Web is an extension of the current Web  that allows the meaning of information to be precisely described in terms of well-defined vocabularies that are understood by people and computers. On the Semantic Web information is described using a new W3C standard called the Resource Description Framework (RDF). Semantic Web Search is a search engine for the Semantic Web. Current Web sites can be used by both people and computers to precisely locate and gather information published on the Semantic Web. Ontology BIB001 is one of the most important concepts used in the semantic web infrastructure, and RDF(S) (Resource Description Framework/Schema) and OWL (Web Ontology Languages) are two W3C recommended data representation models which are used to represent ontologies. The Semantic Web will support more efficient discovery, automation, integration and reuse of data and provide support for interoperability problem which can not be resolved with current web technologies. Currently research on semantic web search engines are in the beginning stage, as the traditional search engines such as Google, Yahoo, and Bing (MSN) and so forth still dominate the present markets of search engines. Most of the search engines search for keywords to answer the queries from users. The search engines usually search web pages for the required information. However they filter the pages from searching unnecessary pages by using advanced algorithms. These search engines can answer topic wise queries efficiently and effectively by developing state-of art algorithms. However they are vulnerable in answering intelligent queries from the user due to the dependence of their results on information available in web pages. The main focus of these search engines is solving these queries with close to accurate results in small time using much researched algorithms. However, it shows that such search engines are vulnerable in answering intelligent queries using this approach. They either show inaccurate results with this approach or show accurate but (could be) unreliable results. With the keywords based searches they usually provide results from blogs (if available) or other discussion boards. The user cannot have a satisfaction with these results due to lack of trusts on blogs etc. To overcome this problem in search engines to retrieve relevant and meaningful information intelligently, semantic web technology deals with a great role BIB002 . Intelligent semantic technology gives the nearer to desired results by search engines to the user. In this paper, we will make a preliminary survey over the existing literature regarding intelligent semantic search engines and semantic web search. By classifying the literature into few main categories, we review their characteristics respectively. In addition, the issues within the reviewed intelligent semantic search methods and engines are analyzed and concluded based on perspectives.