Semantic Interation, Text Mining, Tools and Technologies

2015 ◽  
pp. 47-63
Author(s):  
Chandrakant Ekkirala
Keyword(s):  
Text Mining ◽  
Data Integration ◽  
Semantic Integration ◽  
Semantic Technologies ◽  
Integration Technique ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Periodic Data ◽  
Integration Techniques ◽  
Mining Algorithms

Semantic technologies have gained prominence over the last several years. Semantic technologies are explored in detail and semantic integration of data will be outlined. The various data integration techniques and approaches will also be touched upon. Text Mining, different associated algorithms and the various tools and technologies used in text mining will be enumerated in detail. The chapter will have the following sections – 1. Data Integration Techniques • Data Integration Technique – Extraction, Transformation and Loading (ETL) • Data Integration Technique – Data Federation 2. Data Integration Approaches • Need Based Data Integration • Periodic Data Integration • Continuous Data Integration 3. Semantic Integration 4. Semantic Technologies 5. Semantic Web Technologies 6. Text Mining 7. Text Mining Algorithms 8. Tools and Technologies for Text Mining

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.

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.

scholarly journals The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies

2013 ◽  
Vol 4 (1) ◽  
pp. 6 ◽  
Author(s):  
Toshiaki Katayama ◽  
Mark D Wilkinson ◽  
Gos Micklem ◽  
Shuichi Kawashima ◽  
Atsuko Yamaguchi ◽  
...  
Keyword(s):  
Semantic Web ◽  
Data Integration ◽  
Life Science ◽  
Science Data ◽  
Semantic Web Technologies ◽  
Web Technologies

Semantic Middleware Architecture

2013 ◽  
Vol 436 ◽  
pp. 488-496 ◽  
Author(s):  
Dragos Repta ◽  
Ioan Stefan Sacala ◽  
Mihnea Moisescu ◽  
Aurelian Mihai Stanescu
Keyword(s):  
Distributed Systems ◽  
Internet Of Things ◽  
Test System ◽  
Context Aware ◽  
Semantic Technologies ◽  
Research Activity ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
It Systems ◽  
Event Based

Some of the most important features of future IT systems will come from the current research of Semantic Web technologies and distributed systems. Following this idea we set out to implement a middleware solution that builds upon the latest developments of research activity into Internet of Things and, more generally, context-aware systems. These directions where selected because they currently are the main drivers of the research into the applications of semantic technologies. Our focus was mainly on the aspects that we considered to be overlooked by other proposed semantic middleware solutions, such as the support of asynchronous, event based communication and ontology management in distributed systems. The developed middleware was used to build a test system in order to prove its advantages over similar systems that rely on currently used technologies.

A State of the Art on Big Data With Semantic Web Technologies

2020 ◽  
pp. 195-216
Author(s):  
Satyaveer Singh ◽  
Mahendra Singh Aswal
Keyword(s):  
Big Data ◽  
Semantic Web ◽  
Database Management ◽  
High Volume ◽  
Semantic Technologies ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
The Past ◽  
Digital World ◽  
Data Heterogeneity

We live in a digital world where a large amount of data is being generated rapidly by various diverse sources with an unprecedented rate. The term Big Data has been coined to represent a large amount of data. But Big Data could not be processed and analysed by traditional database management systems. A number of challenges such as data heterogeneity and diversity are being faced by enterprises due to high volume, variety, and velocity of Big Data. Since the past few years, some research efforts have been attempted to integrate semantic web technologies such as ontologies with Big Data. This integration is paving the way to deal with various issues that are related to the processing of Big Data. This chapter firstly uncovers the fundamentals of Big Data, its characteristics and opportunities, challenges, related current tools, and technologies. Secondly, it tries to highlight the integration of Big Data with semantic web technologies. The promising research is going on to tackle volume and velocity of Big Data by using semantic technologies.

Applicability Assessment of Semantic Web Technologies in Human Resources Domain

2012 ◽  
pp. 470-485
Author(s):  
Valentina Janev ◽  
Sanja Vraneš
Keyword(s):  
Information Systems ◽  
Semantic Web ◽  
Human Resources ◽  
Business Processes ◽  
Global Market ◽  
Semantic Technologies ◽  
Enterprise Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Illustrative Case Study

To meet the challenges of today’s Internet economy and be competitive in a global market, enterprises are constantly adapting their business processes and adjusting their information systems. In this article, the authors analyze the applicability and benefits of using semantic technologies in contemporary information systems. By using an illustrative case study of deployment of Semantic Web technologies in Human Resources sector at the Mihajlo Pupin Institute, this paper shows how the latest semantic technologies could be used with existing Enterprise Information Systems and Enterprise Content Management systems to ensure meaningful search and retrieval of expertise for in-house users as well as for integration in the European research space and beyond.

scholarly journals A literature review of current technologies on health data integration for patient-centered health management

2019 ◽  
Vol 26 (3) ◽  
pp. 1926-1951
Author(s):  
Cong Peng ◽  
Prashant Goswami ◽  
Guohua Bai
Keyword(s):  
Literature Review ◽  
Data Integration ◽  
Web Application ◽  
Health Management ◽  
Application Programming Interface ◽  
Health Data ◽  
Patient Centered ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Application Programming

Health data integration enables a collaborative utilization of data across different systems. It not only provides a comprehensive view of a patient’s health but can also potentially cope with challenges faced by the current healthcare system. In this literature review, we investigated the existing work on heterogeneous health data integration as well as the methods of utilizing the integrated health data. Our search was narrowed down to 32 articles for analysis. The integration approaches in the reviewed articles were classified into three classifications, and the utilization approaches were classified into five classifications. The topic of health data integration is still under debate and problems are far from being resolved. This review suggests the need for a more efficient way to invoke the various services for aggregating health data, as well as a more effective way to integrate the aggregated health data for supporting collaborative utilization. We have found that the combination of Web Application Programming Interface and Semantic Web technologies has the potential to cope with the challenges based on our analysis of the review result.

Applicability Assessment of Semantic Web Technologies in Human Resources Domain

2010 ◽  
Vol 23 (3) ◽  
pp. 27-42 ◽  
Author(s):  
Valentina Janev ◽  
Sanja Vraneš
Keyword(s):  
Information Systems ◽  
Semantic Web ◽  
Human Resources ◽  
Business Processes ◽  
Content Management ◽  
Global Market ◽  
Illustrative Case ◽  
Semantic Technologies ◽  
Semantic Web Technologies ◽  
Web Technologies

To meet the challenges of today’s Internet economy and be competitive in a global market, enterprises are constantly adapting their business processes and adjusting their information systems. In this article, the authors analyze the applicability and benefits of using semantic technologies in contemporary information systems. By using an illustrative case study of deployment of Semantic Web technologies in Human Resources sector at the Mihajlo Pupin Institute, this paper shows how the latest semantic technologies could be used with existing Enterprise Information Systems and Enterprise Content Management systems to ensure meaningful search and retrieval of expertise for in-house users as well as for integration in the European research space and beyond.

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