Semantic Web Search Engine

International Journal of Engineering Research and Technology (IJERT), 2015

https://www.ijert.org/semantic-web-search-engine https://www.ijert.org/research/semantic-web-search-engine-IJERTV4IS040908.pdf The World Wide Web (WWW) allows people to share information or data from the large database repositories globally. We need to search the information with specialized tools known generically as search engines. There are many search engines available today, where retrieving meaningful information is difficult. However to overcome this problem of retrieving meaningful information intelligently in common search engines, semantic web technologies are playing a major role. In this paper we present a different implementation of semantic search engine and the role of semantic relatedness to provide relevant results. The concept of Semantic Relatedness is connected with Wordnet which is a lexical database of words. We also made use of TF-IDF algorithm to calculate word frequency in each and every webpage and Keyword Extraction in order to extract only useful keywords from a huge set of words. These algorithms are used to retrieve much optimized and useful results to the user.

Journal of emerging technologies and innovative research, 2015

The main idea of this paper is to show current state of the Semantic Web concept. The large growth in the volume of data and with the extreme growth of web pages, today's search engines are not suitable anymore. Search engine is the most important tool to find any information in World Wide Web. Most existing Web search engines only generate a result list matching the user's query accurately. Based on extremely large and dynamic source of information, both normal and professional users obtain relevant information from information retrieval system with respect to the query that expresses the user's needs. Semantic Search Engine is born of traditional search engine to overcome the above problem. The Semantic Web is added advance features of the current web in which information is given well-defined meaning. Every page in semantic web contains semantic metadata that holds additional information's about the Web page. In this paper we made a brief survey on various assure ...

Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication - ICUIMC '13, 2013

Discovery of World Wide Web data is slightly affected due to natural-language text presentation in the internet. Moreover, exponential growth of users' requirement and expectation makes the matter more critical. Coping with the overstated problem, research and development on the Semantic Web and Semantic Web search engine are actively conducted. The concept of ontology is established in the searching process. In this paper, LexOn Search is introduced using WordNet as a lexical ontology to presents clustering concept in order to utilized searching time. LexOn search engine is built by integrating WordNet, Apache Solr and Semantic Information Retrieval Engine (SIREn). We test the LexOn search with SIREn and it shows LexOn improved the searching time. The preliminary experimental results have given interesting results in terms of data arrangement and time usage.

International Journal of Computer Applications, 2012

Information retrieval (IR) is the area of study concerned with searching documents or information within documents. The user describes information needs with a query which consists of a number of words. Finding weight of a query term is useful to determine the importance of a query. Calculating term importance is fundamental aspect of most information retrieval approaches and it is traditionally determined through Term Frequency-Inverse Document Frequency (IDF). This paper proposes a new term weighting technique called concept-based term weighting (CBW) to give a weight for each query term to determine its significance by using WordNet Ontology.

International Journal of Computer Applications, 2015

Current World Wide Web also recognized as Web 2.0 is an immense library of interlinked documents that are transferred by computers and presented to people. Search engine is considered the most important tool to discover any information from WWW. Inspite of having lots of development and novel research in current search engines techniques, they are still syntactic in nature and display search results on the basis of keyword matching without understanding the meaning of query, resulting in the production of list of WebPages containing a large number of irrelevant documents as an output. Semantic Web (Web 3.0), the next version of World Wide Web is being developed with the aim to reduce the problem faced in Web 2.0 by representing data in structured form and to discover such data from Semantic Web, Semantic Search Engines (SSE) are being developed in many domains. This paper provides a survey on some of the prevalent SSEs focusing on their architecture; and presents a comparative study on the basis of technique they follow for crawling, reasoning, indexing, ranking etc.

The Web search engines plays a critical role in the mining of data from the large number of web information's in the form of web pages. The existing Semantic web search engines are failed to retrieve the web pages with the desired amount of accuracy. The ranking needs to work on whole of the annotated knowledge database. The proposed system uses the layered architecture which will increase the information retrieval accuracy using relations. But in this relation-based page rank algorithm to be used in conjunction with Semantic web search engine. It emphasize on the information extracted from the user queries on annotated resources. Relevance between queries is measured in terms of probability that a retrieved resource actually contains the relations based on the user query. It tends to produce results in terms of both time complexity and accuracy.

2012

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 ...

The promise of semantic technology presents a better search scenario than traditional/keyword based search engines for applications and knowledge discovery. As the society is transforming into knowledge society, the power of information is increasingly becoming crucial for decision making process and business solutions. Thus, semantic technology is applied to enhance the visibility of content created in different form and publishing them, data coupling through semantic links, forming communities, provenance of concepts and validation, disambiguation and authentication of terms with semantic etc. Feature based analysis has been done with examples on two different semantic web search engines.

2019

With the rapid development of the World Wide Web, one of the main tools for people to get network information is search engine. However, the search results are widely condemned due to the lack of accuracy and redundancy disadvantages. The semantic web is a technology to save data in a machine-readable format that makes it possible for the machines to intelligently match that data with related data based on its semantics. This paper starts from the traditional search engine, and firstly introduces its classification, popular technology, advantages, disadvantages, and deep Knowledge on semantic-technology, thus leads to the semantic search engine model.

2012

The tremendous growth in the volume of data and with the terrific growth of number of web pages, traditional search engines now a days are not appropriate and not suitable anymore. Search engine is the most important tool to discover any information in World Wide Web. Semantic Search Engine is born of traditional search engine to overcome the above problem. The Semantic Web is an extension of the current web in which information is given well-defined meaning. Semantic web technologies are playing a crucial role in enhancing traditional web search, as it is working to create machine readable data. but it will not replace traditional search engine. In this paper we made a brief survey on various promising features of some of the best semantic search engines developed so far and we have discussed the various approaches to semantic search. We have summarized the techniques, advantages of some important semantic web search engines that are developed so far.The most prominent part is that how the semantic search engines differ from the traditional searches and their results are shown by giving a sample query as input.