The use of web search engines is an essential part of the ordinary life. It is difficult to underestimate the tremendous role they have for internet users. Over the years several useful web-based search engines such as Lycos, Excite, AltaVista, Google, Yahoo, Bing and the likes emerge. This work gives an insight into the trend of web-based search engine, diverse ways in which it works, and its future.

Trends in Web-Based Search Engine

The incredible progress in the size of data and with the great growth of the amount of web pages, outdated search engines are not suitable and not properly any longer. The search engine is the best significant device to determine any information in World Wide Web. Semantic Search Engine is innate of outdated search engine to solve the above problem. The Semantic Web is a postponement of the existing web where data is are given in fixed meaning. Semantic web tools have a vital role in improving web search, because it is functioning to produce machine readable data and semantic web technologies will not exchange traditional search engine

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An effective framework to improve the efficiency of semantic based search

Electronic learning, commonly called e-learning, has the goal of using technology to spread knowledge. Actually, the fast growing of Internet has allowed the creation of a variety of e-learning platforms. Thus there is the need for the regulation and interoperation of these platforms. Interoperability is a key factor in e-learning systems because it allows exchange and reuse of educational resources developed in different platforms. Problems may appear in their design and implementation because of the lack of interoperability among educative platforms contents. For that reason, it is important to use meaningful information to make possible the interoperability among different environments and to help in the management of proper contents. This is the area where Semantic Web may play a key role for reaching this goal. In this work, we propose the design of an e-learning platform prototype, that using semantic meaning, helps in the solution of interoperability problems.

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A Proposal of an E-Learning Inter-Operable Platform Based on Semantic Web

Ontology based search engine is a tool that helps you in retrieving required information from the web by only considering the logical denotation of the submitted query. The semantic based search engines are the annotated form of the ontology based search engines. The paper identifies various methods involved in determination and identification of various ontology based search engines. The search engines types discussed in the paper is broadly classified into keyword based search engine and semantic based search engine. Majorly the efficiency of both the kind of search engines is taken into consideration here. In paper (1) the fuzzy ontology modelling is the main feature. This method is done to find the exact meaning and the relationship between the queries submitted by the user. The fuzzy logic that has been implemented will provide the accurate meaning between them in collaborative sequence. In paper (2) there has been a comparison made between keyword and semantic based search engines. In paper (3) for identifying the relationship, the concept is split into two. They are content concept and location concept. Here for the location concept, the external GPS method is used. In paper (4) multi crawler concepts are used. In this paper, a survey is presented about ontology based search engines and the need for the user's migration to it.

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An Analytic Report on Ontology Based Search Engine

In today's scenario, due to the rapid growth of content volume over the internet, the conventional search engines hardly do afford the required content relevant to the user's query. This can be effectively solved by enforcing semantic web search methodologies. On addressing that, this paper proposed an efficient prototype Relevancy - based Semantic Search E ngine (RSSE). Moreover, the framework enables the users to locate relevant resources and services through semantics and domain expert ise. A novel algorithm called Query Similarity Prediction Algorithm (QSPA) has been developed for proficient information retrieval with minimized processing time consumption and simultaneously, serving multiple remote users. Ranking is also performed based on the relevance score of retrieved documents to aid users for finding which documents are most likely to be relevant documents to the given queries. The experimental results reveal the efficiency of the proposed work with respect to the parameters such a s precision, recall, F - measure, and time required to retrieve the results for queries. (Sridharan. K, M. Chitra. RSSE: A Paradigm for Proficient Information Retrieval using Semantic Web . Life Sci J 2013;10(7s): 4 18 - 425 ) (ISSN:1097 - 8135). http://www.lifesciencesite.com .

http://www.lifesciencesite.com/lsj/life1007s/064_17481life1007s_418_425.pdf

RSSE: A Paradigm for Proficient Information Retrieval using Semantic Web

AS WE KNOW THAT WWW IS ALLOWING PEOPLES TO SHARE THE HUGE INFORMATION GLOBALLY FROM THE BIG DATABASE REPOSITORIES. THE AMOUNT OF INFORMATION GROWS BILLIONS OF DATABASES. HENCE TO SEARCH PARTICULAR INFORMATION FROM THESE HUGE DATABASES WE NEED THE SPECIALIZED MECHANISM WHICH HELPS TO RETRIEVE THAT INFORMATION EFFICIENTLY. NOW DAYS VARIOUS TYPES OF SEARCH ENGINES ARE AVAILABLE WHICH MAKES INFORMATION RETRIEVING IS DIFFICULT. BUT TO PROVIDE THE BETTER SOLUTION TO THIS PROBLEM, SEMANTIC WEB SEARCH ENGINES ARE PLAYING VITAL ROLE. BASICALLY MAIN AIM OF THIS KIND OF SEARCH ENGINES IS TO PROVIDING THE REQUIRED INFORMATION IS SMALL TIME WITH MAXIMUM ACCURACY. BUT THE PROBLEM WITH SEMANTIC SEARCH ENGINES IS THAT THOSE ARE VULNERABLE WHILE ANSWERING THE INTELLIGENT QUERIES. THESE KINDS OF SEARCH ENGINES DON’T HAVE MUCH EFFICIENCY AS PER EXPECTATIONS BY END USERS, AS MOST OF TIME THEY ARE PROVIDING THE INACCURATE INFORMATION’S. THUS IN THIS PAPER WE ARE PRESENTING THE NEW APPROACH FOR SEMANTIC SEARCH ENGINES WHICH WILL ANSWER THE INTELLIGENT QUERIES ALSO MORE EFFICIENTLY AND ACCURATELY. WITH THE

Vishal Khatri

Papers

Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines