Survey Paper on Semantic Web

2018 ◽  
pp. 114-119
Author(s):  
Rimpal Unadkat
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
World Wide ◽  
Web Pages ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Survey Paper ◽  
The People

The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The tremendous growth in the volume of data and with the terrific growth of number of web pages, traditional search engines now 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. However, to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper the authors present survey on the role of search engines in intelligent web, Background, Challenges and some issues.

Survey Paper on Semantic Web

2015 ◽  
Vol 7 (4) ◽  
pp. 13-17 ◽  
Author(s):  
Rimpal Unadkat
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
World Wide ◽  
Web Pages ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Survey Paper ◽  
The People

The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The tremendous growth in the volume of data and with the terrific growth of number of web pages, traditional search engines now 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. However, to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper the authors present survey on the role of search engines in intelligent web, Background, Challenges and some issues.

Survey Paper on Semantic Web

Web Services ◽  
2019 ◽  
pp. 2138-2143
Author(s):  
Rimpal Unadkat
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
World Wide ◽  
Web Pages ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Survey Paper ◽  
The People

The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The tremendous growth in the volume of data and with the terrific growth of number of web pages, traditional search engines now 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. However, to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper the authors present survey on the role of search engines in intelligent web, Background, Challenges and some issues.

scholarly journals Semantic Web Search Engines : A Comparative Survey

2019 ◽  
pp. 107-115
Author(s):  
Anita Kumari ◽  
Jawahar Thakur
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Retrieval System ◽  
Relevant Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Web Search Engine ◽  
Comparative Survey

Search engines play important role in the success of the Web. Search engine helps the users to find the relevant information on the internet. Due to many problems in traditional search engines has led to the development of semantic web. Semantic web technologies are playing a crucial role in enhancing traditional search, as it work to create machines readable data and focus on metadata. However, it will not replace traditional search engines. In the environment of semantic web, search engine should be more useful and efficient for searching the relevant web information. It is a way to increase the accuracy of information retrieval system. This is possible because semantic web uses software agents; these agents collect the information, perform relevant transactions and interact with physical devices. This paper includes the survey on the prevalent Semantic Search Engines based on their advantages, working and disadvantages and presents a comparative study based on techniques, type of results, crawling, and indexing.

Overview of MERA

2019 ◽  
pp. 219-245
Author(s):  
Daniel Fernández-Álvarez ◽  
José Emilio Labra Gayo ◽  
Daniel Gayo-Avello ◽  
Patricia Ordoñez de Pablos
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
World Wide ◽  
Poor Performance ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Matching Process ◽  
Large Databases ◽  
The World ◽  
Distinguishing Features

The proliferation of large databases with potentially repeated entities across the World Wide Web drives into a generalized interest to find methods to detect duplicated entries. The heterogeneity of the data cause that generalist approaches may produce a poor performance in scenarios with distinguishing features. In this paper, we analyze the particularities of music related-databases and we describe Musical Entities Reconciliation Architecture (MERA). MERA consists of an architecture to match entries of two sources, allowing the use of extra support sources to improve the results. It makes use of semantic web technologies and it is able to adapt the matching process to the nature of each field in each database. We have implemented a prototype of MERA and compared it with a well-known music-specialized search engine. Our prototype outperforms the selected baseline in terms of accuracy.

scholarly journals MACHINE LEARNING BASED SEARCH ENGINE WITH CRAWLING, INDEXING AND RANKING

2021 ◽  
Vol 10 (7) ◽  
pp. 76-83
Author(s):  
Anuradha T ◽  
Tayyaba Nousheen
Keyword(s):  
Machine Learning ◽  
World Wide Web ◽  
Search Engine ◽  
Search Engines ◽  
World Wide ◽  
Accurate Result ◽  
Web Pages ◽  
The Web

The web is the heap and huge collection of wellspring of data. The Search Engine are used for retrieving the information from World Wide Web (WWW). Search Engines are helpful for searching user keywords and provide the accurate result in fraction of seconds. This paper proposed Machine Learning based search engine which will give more relevant user searches in the form of web pages. To display the user entered query search engine plays a major role of basic interface. Every site comprises of the heaps of site pages that are being made and sent on the server.

Classification of Semantic Web Technologies

2011 ◽  
pp. 545-555 ◽  
Author(s):  
Rui G. Pereira ◽  
Mário M. Freire
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Real World ◽  
World Wide ◽  
Research Area ◽  
Full Potential ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Research Areas ◽  
The Web

Semantic Web is the name of the next generation World Wide Web, that has been recently proposed by Tim Berners-Lee and the World Wide Web Consortium (W3C)1. In this new Web architecture, information and Web services will be easily understandable and usable by both humans and computers. The objective is not to make computers understand the human language, but to define a universal model for the expression of the information and a set of inference rules that machines can easily use in order to process and relate the information as if they really understood it (Berners-Lee, 1998). Though, as the current Web provided sharing of documents among previously incompatible computers, the Semantic Web intends to go beyond, allowing stovepipe systems, hardwired computers, and other devices to share contents embedded in different documents. The most known architecture for Semantic Web is based on a stack of related technologies, each one being a whole research area by itself (Berners-Lee, Hendler, & Lassila. 2001; Pereira & Freire, 2005). Accomplishment of the Semantic Web is considered a great challenge, not only due to the complexity of implementation but also because of the vast applicability in several areas. In spite of this, Semantic Web is still one of the most promising research areas among those which aim to define a new architecture for the Web. Semantic Web goes far beyond previous information retrieval and knowledge representation projects, presenting a non-centralized way to represent and contextualize real-world concepts, unambiguously, for several areas of knowledge. Semantic Web-enabled machines will handle information at our communication level. It is clear that the ability to interpret reality is still very primitive, however, Semantic Web points a way towards machine interaction and learning (Pereira et al., 2005). Semantic Web will integrate, interact with, and bring benefits to most human activities. Its full potential will go beyond the Web to real-world machines, providing increased interaction between machines and with humans—smarter phones, radios, and other electronic devices. Semantic Web will bring a different kind of approach in the understanding of reality by the machines and will constitute a mark in the evolution of human knowledge (Pereira et al., 2005).

Knowledge Representation Technologies Using Semantic Web

Web Services ◽  
2019 ◽  
pp. 1068-1076
Author(s):  
Vudattu Kiran Kumar
Keyword(s):  
Semantic Web ◽  
Crucial Role ◽  
World Wide ◽  
Global Information ◽  
Semantic Technologies ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Repositories ◽  
The World ◽  
The Web

The World Wide Web (WWW) is global information medium, where users can read and write using computers over internet. Web is one of the services available on internet. The Web was created in 1989 by Sir Tim Berners-Lee. Since then a great refinement has done in the web usage and development of its applications. Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. Semantic web is not a separate web it is an extension to the current web with additional semantics. Semantic technologies play a crucial role to provide data understandable to machines. To achieve machine understandable, we should add semantics to existing websites. With additional semantics, we can achieve next level web where knowledge repositories are available for better understanding of web data. This facilitates better search, accurate filtering and intelligent retrieval of data. This paper discusses about the Semantic Web and languages involved in describing documents in machine understandable format.

OWL

2011 ◽  
pp. 3009-3017
Author(s):  
Adélia Gouveia ◽  
Jorge Cardoso
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Particle Physics ◽  
World Wide ◽  
Visual Presentation ◽  
Web Pages ◽  
Markup Language ◽  
Extensible Markup ◽  
Description Framework ◽  
The Web

The World Wide Web (WWW) emerged in 1989, developed by Tim Berners-Lee who proposed to build a system for sharing information among physicists of the CERN (Conseil Européen pour la Recherche Nucléaire), the world’s largest particle physics laboratory. Currently, the WWW is primarily composed of documents written in HTML (hyper text markup language), a language that is useful for visual presentation (Cardoso & Sheth, 2005). HTML is a set of “markup” symbols contained in a Web page intended for display on a Web browser. Most of the information on the Web is designed only for human consumption. Humans can read Web pages and understand them, but their inherent meaning is not shown in a way that allows their interpretation by computers (Cardoso & Sheth, 2006). Since the visual Web does not allow computers to understand the meaning of Web pages (Cardoso, 2007), the W3C (World Wide Web Consortium) started to work on a concept of the Semantic Web with the objective of developing approaches and solutions for data integration and interoperability purpose. The goal was to develop ways to allow computers to understand Web information. The aim of this chapter is to present the Web ontology language (OWL) which can be used to develop Semantic Web applications that understand information and data on the Web. This language was proposed by the W3C and was designed for publishing, sharing data and automating data understood by computers using ontologies. To fully comprehend OWL we need first to study its origin and the basic blocks of the language. Therefore, we will start by briefly introducing XML (extensible markup language), RDF (resource description framework), and RDF Schema (RDFS). These concepts are important since OWL is written in XML and is an extension of RDF and RDFS.

Knowledge Representation Technologies Using Semantic Web

2017 ◽  
pp. 158-166
Author(s):  
Vudattu Kiran Kumar
Keyword(s):  
Semantic Web ◽  
Crucial Role ◽  
World Wide ◽  
Global Information ◽  
Semantic Technologies ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Repositories ◽  
The World ◽  
The Web

The World Wide Web (WWW) is global information medium, where users can read and write using computers over internet. Web is one of the services available on internet. The Web was created in 1989 by Sir Tim Berners-Lee. Since then a great refinement has done in the web usage and development of its applications. Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. Semantic web is not a separate web it is an extension to the current web with additional semantics. Semantic technologies play a crucial role to provide data understandable to machines. To achieve machine understandable, we should add semantics to existing websites. With additional semantics, we can achieve next level web where knowledge repositories are available for better understanding of web data. This facilitates better search, accurate filtering and intelligent retrieval of data. This paper discusses about the Semantic Web and languages involved in describing documents in machine understandable format.

A Review on Semantic Text and Multimedia Retrieval and Recent Trends

2015 ◽  
Vol 6 (1) ◽  
pp. 54-74
Author(s):  
Oğuzhan Menemencioğlu ◽  
İlhami Muharrem Orak
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
Semantic Search ◽  
Multimedia Retrieval ◽  
Web Pages ◽  
The Face ◽  
Recent Trends ◽  
New Applications ◽  
Machine Readable

Semantic web works on producing machine readable data and aims to deal with large amount of data. The most important tool to access the data which exist in web is the search engine. Traditional search engines are insufficient in the face of the amount of data that consists in the existing web pages. Semantic search engines are extensions to traditional engines and overcome the difficulties faced by them. This paper summarizes semantic web, concept of traditional and semantic search engines and infrastructure. Also semantic search approaches are detailed. A summary of the literature is provided by touching on the trends. In this respect, type of applications and the areas worked for are considered. Based on the data for two different years, trend on these points are analyzed and impacts of changes are discussed. It shows that evaluation on the semantic web continues and new applications and areas are also emerging. Multimedia retrieval is a newly scope of semantic. Hence, multimedia retrieval approaches are discussed. Text and multimedia retrieval is analyzed within semantic search.

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