Rule-based information extraction for mechanical-electrical-plumbing-specific semantic web

In this paper, the need for the right information for patients with chronic diseases is elaborated, followed by some scenarios of how the semantic web can be utilised to retrieve useful and precise information by stakeholders. In previous work, the author has demonstrated the automation of knowledge acquisition from the current web is becoming an important step towards this goal. The aim was twofold; first to learn what types of information exist in chronic disease-related websites, and secondly how to extract and structure such information into machine understandable form. It has been shown that these websites exhibit many common concepts which resulted in the construction of the ontology to guide in extracting information for new unseen websites. Also, the study has resulted in the development of a platform for information extraction that utilises the ontology. Continuous work has opened many issues which are disussed in this paper. While further work is still needed, the experiments to date have shown encouraging results.

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Creating a Policy-Aware Web

Global Information Technologies ◽

10.4018/978-1-59904-939-7.ch008 ◽

2008 ◽

pp. 81-100

Author(s):

Daniel J. Weitzner ◽

Jim Hendler ◽

Tim Berners-Lee ◽

Dan Connolly

Keyword(s):

Semantic Web ◽

Management System ◽

World Wide ◽

Theorem Prover ◽

Future Research ◽

Policy Management ◽

Rule Based ◽

The World ◽

The Web ◽

Current Mechanism

In this chapter, we describe the motivations for, and development of, a rule-based policy management system that can be deployed in the open and distributed milieu of the World Wide Web. We discuss the necessary features of such a system in creating a “Policy Aware” infrastructure for the Web and argue for the necessity of such infrastructure. We then show how the integration of a Semantic Web rules language (N3) with a theorem prover designed for the Web (Cwm) makes it possible to use the Hypertext Transport Protocol (http) to provide a scalable mechanismfor the exchange of rules and, eventually, proofs for access control on the Web. We also discuss which aspects of the Policy Aware Web are enabled by the current mechanism and describe future research needed to make the widespread deployment of rules and proofs on the Web a reality.

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Explaining Semantic Web Applications

Web Technologies ◽

10.4018/978-1-60566-982-3.ch119 ◽

2011 ◽

pp. 2304-2327

Author(s):

Deborah L. McGuinness ◽

Vasco Furtado ◽

Paulo Pinheiro da Silva ◽

Li Ding ◽

Alyssa Glass ◽

...

Keyword(s):

Semantic Web ◽

Information Extraction ◽

Web Applications ◽

Deductive Reasoning ◽

Learning Systems ◽

Full Potential ◽

Integrated Learning ◽

Integrated Learning Systems ◽

The One

In this chapter, we introduce the concept of explanation for Semantic Web applications by providing motivation, description, and examples. We describe the Inference Web explanation toolkit that provides support for a broad range of explanation tasks ranging from explaining deductive reasoning, to information extraction, to hybrid integrated learning systems. We argue that an explanation solution such as the one we endorse is required if we are to realize the full potential of hybrid, distributed, intelligent Web agents that users can trust and use.

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Search Engine-Based Web Information Extraction

Web Technologies ◽

10.4018/978-1-60566-982-3.ch109 ◽

2011 ◽

pp. 2048-2081

Author(s):

Gijs Geleijnse ◽

Jan Korst

Keyword(s):

Semantic Web ◽

Information Extraction ◽

Search Engine ◽

Community Based ◽

Web Information Extraction ◽

Structure Information ◽

Web Information ◽

Structured Information ◽

The Web ◽

Standard Semantic

In this chapter we discuss approaches to find, extract, and structure information from natural language texts on the Web. Such structured information can be expressed and shared using the standard Semantic Web languages and hence be machine interpreted. In this chapter we focus on two tasks in Web information extraction. The first part focuses on mining facts from the Web, while in the second part, we present an approach to collect community-based meta-data. A search engine is used to retrieve potentially relevant texts. From these texts, instances and relations are extracted. The proposed approaches are illustrated using various case-studies, showing that we can reliably extract information from the Web using simple techniques.

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