A Web-Based Method for Ontology Population

The Semantic Web, proposed by Berners-Lee, aims to make explicit the meaning of the data available on the Internet, making it possible for Web data to be processed both by people and intelligent agents. The Semantic Web requires Web data to be semantically classified and annotated with some structured representation of knowledge, such as ontologies. This chapter proposes an unsupervised, domain-independent method for extracting instances of ontological classes from unstructured data sources available on the World Wide Web. Starting with an initial set of linguistic patterns, a confidence-weighted score measure is presented integrating distinct measures and heuristics to rank candidate instances extracted from the Web. The results of several experiments are discussed achieving very encouraging results, which demonstrate the feasibility of the proposed method for automatic ontology population.

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Semantic E-Business Challenges and Directions

Encyclopedia of Networked and Virtual Organizations ◽

10.4018/978-1-59904-885-7.ch187 ◽

2011 ◽

pp. 1421-1428

Author(s):

Giorgos Laskaridis ◽

Konstantinos Markellos ◽

Penelope Markellou ◽

Angeliki Panayiotaki ◽

Athanasios Tsakalidis

Keyword(s):

Semantic Web ◽

World Wide ◽

Business Processes ◽

Semantic Knowledge ◽

Web Based ◽

The World ◽

Extensible Markup ◽

Description Framework ◽

Business Challenges ◽

Resource Description

The emergence of semantic Web opens up boundless new opportunities for e-business. According to Tim Berners-Lee, Hendler, and Lassila (2001), “the semantic Web is an extension of the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation”. A more formal definition by W3C (2001) refers that, “the semantic Web is the representation of data on the World Wide Web. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners. It is based on the resource description framework (RDF), which integrates a variety of applications using eXtensible Markup Language (XML) for syntax and uniform resource identifiers (URIs) for naming”. The capability of the semantic Web to add meaning to information, stored in such way that it can be searched and processed as well as recent advances in semantic Web-based technologies provide the mechanisms for semantic knowledge representation, exchange and collaboration of e-business processes and applications.

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SWBDS: Web Data Sources Management Infrastructure for Semantic Web Applications

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.186.438 ◽

2011 ◽

Vol 186 ◽

pp. 438-442

Author(s):

Lin Hua Zhou ◽

Jian Bo Fan ◽

Ke Jia He

Keyword(s):

Semantic Web ◽

Web Applications ◽

Domain Ontology ◽

Data Sources ◽

Data Service ◽

Web Data ◽

Web Based ◽

Complex Queries ◽

Human Effort ◽

Legacy Applications

The Semantic Web envisions a World Wide Web in which datasources are encapsulated and described with rich semantics, and demander can issue complex queries. A critical problem in the situation is how to efficiently describe, organize and search these encapsulated datasources. This paper describes the Semantic Web-Based Data service(SWBDS for short) approach, which addresses these challenges. SWBDS introduces an ontology-based approach to, mapping web data sources to data service (DS for short), publishing DS with the shared domain ontology, and answering queries through DS provided interface. We define the domain ontology to illustrate the DS interface. The domain ontology is described in OWL that can be understood and processed by machines. Therefore, SWBDS can provide reasoning functions and facilitate datasources management with little human effort. This new system model makes full use of legacy applications and is flexible for future extensions.

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Semantic E-Business

Advances in Semantic Web and Information Systems - Semantic Web-Based Information Systems ◽

10.4018/978-1-59904-426-2.ch009 ◽

2011 ◽

pp. 214-233

Author(s):

Rahul Singh ◽

Lakshmi Iyer ◽

A. F. Salam

Keyword(s):

Semantic Web ◽

Intelligent Agents ◽

Business Models ◽

Business Processes ◽

Heterogeneous Systems ◽

Organizational Boundaries ◽

Semantic Web Technologies ◽

Web Based ◽

Web Technologies ◽

Technical Architecture

We define semantic e-business as “an approach to managing knowledge for coordination of e-business processes through the systematic application of Semantic Web technologies.” Advances in Semantic Web-based technologies offer the means to integrate heterogeneous systems across organizations in a meaningful way by incorporating ontology — a common, standard, and shareable vocabulary used to represent the meaning of system entities; knowledge representation, with structured collections of information and sets of inference rules that can be used to conduct automated reasoning; and intelligent agents that collect content from diverse sources and exchange semantically enriched information. These primary components of the Semantic Web vision form the foundation technology for semantic e-business. The challenge for research in information systems and e-business is to provide insight into the design of business models and technical architecture that demonstrate the potential of technical advancements in the computer and engineering sciences to be beneficial to business and consumers. Semantic e-business seeks to apply fundamental work done in Semantic Web technologies to support the transparent flow of semantically enriched information and knowledge — including content and know-how — to enable, enhance, and coordinate collaborative e-business processes within and across organizational boundaries. Semantic e-business processes are characterized by the seamless and transparent flow of semantically enriched informationand knowledge. We present a holistic view of semantic e-business that integrates emergent and well-grounded Semantic Web technologies to improve the current state of the art in the transparency of e-business processes.

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Semantic E-Business

Electronic Business ◽

10.4018/978-1-60566-056-1.ch004 ◽

2009 ◽

pp. 44-58

Author(s):

Rahul Singh ◽

Lakshmi Iyer ◽

A.F. Salam

Keyword(s):

Semantic Web ◽

Intelligent Agents ◽

Business Models ◽

Heterogeneous Systems ◽

Organizational Boundaries ◽

Semantic Web Technologies ◽

Web Based ◽

Web Technologies ◽

Technical Architecture ◽

Work Done

We define Semantic eBusiness as “an approach to managing knowledge for coordination of eBusiness processes through the systematic application of Semantic Web technologies.” Advances in Semantic Web-based technologies offer the means to integrate heterogeneous systems across organizations in a meaningful way by incorporating ontology—a common, standard, and shareable vocabulary used to represent the meaning of system entities; knowledge representation, with structured collections of information and sets of inference rules that can be used to conduct automated reasoning; and intelligent agents that collect content from diverse sources and exchange semantically enriched information. These primary components of the Semantic Web vision form the foundation technology for semantic eBusiness. The challenge for research in information systems and eBusiness is to provide insight into the design of business models and technical architecture that demonstrate the potential of technical advancements in the computer and engineering sciences to be beneficial to business and consumers. Semantic eBusiness seeks to apply fundamental work done in Semantic Web technologies to support the transparent flow of semantically enriched information and knowledge—including content and know-how—to enable, enhance, and coordinate collaborative eBusiness processes within and across organizational boundaries. Semantic eBusiness processes are characterized by the seamless and transparent flow of semantically enriched information and knowledge. We present a holistic view of semantic eBusiness that integrates emergent and well-grounded Semantic Web technologies to improve the current state of the art in the transparency of eBusiness processes.

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A survey on automatically constructed universal knowledge bases

Journal of Information Science ◽

10.1177/0165551520921342 ◽

2020 ◽

pp. 016555152092134

Author(s):

Bayzid Ashik Hossain ◽

Abdus Salam ◽

Rolf Schwitter

Keyword(s):

Semantic Web ◽

Automated Reasoning ◽

World Wide ◽

Knowledge Bases ◽

Generation Process ◽

Practical Applications ◽

The World ◽

Real World Applications ◽

Low Coverage ◽

Domain Independent

A universal knowledge base can be defined as a domain-independent ontology containing instances. Ontologies define the concepts and relations among these concepts and are used to represent a domain of interest. These universal knowledge bases are the elementary units for automated reasoning on the Semantic Web. The Semantic Web is an extension of the World Wide Web which facilitates software agents to share content beyond the limitations of applications and websites. This survey focuses on the most prominent automatically constructed universal knowledge bases including KnowItAll, DBpedia, YAGO, NELL, Probase, BabelNet and Knowledge Vault. We take a closer look at how these knowledge bases are built, in particular at the information extraction and taxonomy generation process and investigate how they are used in practical applications. Due to quality concerns, the most successful and widely employed knowledge bases are manually constructed to maintain high quality, but they suffer from low coverage, high assembly and quality assurance cost. On the contrary, automatic approaches for building knowledge bases try to overcome these drawbacks. Although it is strenuous to achieve the same level of quality as for manual knowledge bases, we found that the surveyed automatically constructed knowledge bases have shown promising results and are useful for many real-world applications.

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