[1]Ontology-based semantic matchmaking approach
Gao Shu a,*, Omer F. Rana b, Nick J. Avis b, Chen Dingfang a
Abstract
As a greater number of Web Services are made available, support for service discovery mechanisms become essential. Services can
have quite different Quality of Service characteristics (such as their response time when given a particular set of data). A service requestor
therefore requires more sophisticated approaches to find a service that meets a particular behavior, because supporting matching between
a service request and properties is not straightforward. Matchmaking plays a vital role in this discovery process. We propose a novel
matchmaking algorithm to effectively compute the semantic distance of concepts in an ontology. It is based on description logic formalization
and reasoning, extends simple subsumption matching found in other approaches and allows match ranking. We have implemented
[2]Ontology languages for the semantic web:A never completely updated review
J.R.G. Pulido a,¤, M.A.G. Ruiz b, R. Herrera c, E. Cabello d, S. Legrand e, D. Elliman f
Abstract
This paper gives a never completely account of approaches that have been used for the research community for representing
knowledge. After underlining the importance of a layered approach and the use of standards, it starts with early eVorts used for
artiWcial intelligence researchers. Then recent approaches, aimed mainly at the semantic web, are described. Coding examples
from the literature are presented in both sections. Finally, the semantic web ontology creation process, as we envision it, is
introduced.
[3]The Semantic Web and Web Services
David Bell
The Queen’s University of Belfast, Belfast BT7 1NN, UK
E-mail address: da.bell@qub.ac.uk
Christoph Bussler
Digital Enterprise Research Institute (DERI), National University of Ireland, Galway, Galway, Ireland
E-mail address: chris.bussler@deri.org
Jian Yang
Department of Computing Macquarrie University, Sydney, Australia
E-mail address: jian@comp.mq.edu.au
[4]Ontology based text indexing and querying for the semantic web
Jacob Ko¨hler a,*, Stephan Philippi b, Michael Specht c, Alexander Ru¨egg d
a Bioinformatics, BAB, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ, UK
b University of Koblenz, Germany
c RG Statistical Genetics, Max Planck Institute of Psychiatry, Mu¨ nchen, Germany
d Technical Faculty, University of Bielefeld, Germany
Abstract
This publication shows how the gap between theHTMLbased internet and the RDF based vision of the semantic web might be bridged,
by linking words in texts to concepts of ontologies. Most current search engines use indexes that are built at the syntactical level and return
hits based on simple string comparisons. However, the indexes do not contain synonyms, cannot differentiate between homonyms (‘mouse’
as a pointing vs. ‘mouse’ as an animal) and users receive different search results when they use different conjugation forms of the same word.
In this publication, we present a system that uses ontologies and Natural Language Processing techniques to index texts, and thus supports
word sense disambiguation and the retrieval of texts that contain equivalent words, by indexing them to concepts of ontologies.
For this purpose, we developed fully automated methods for mapping equivalent concepts of imported RDF ontologies (for this prototype
WordNet, SUMO and OpenCyc). These methods will thus allow the seamless integration of domain specific ontologies for concept
based information retrieval in different domains.
To demonstrate the practical workability of this approach, a set of web pages that contain synonyms and homonyms were indexed
and can be queried via a search engine like query frontend. However, the ontology based indexing approach can also be used for other
data mining applications such text clustering, relation mining and for searching free text fields in biological databases. The ontology
alignment methods and some of the text mining principles described in this publication are now incorporated into the ONDEX system
http://ondex.sourceforge.net/.
[5]A proof markup language for Semantic Web services
Paulo Pinheiro da Silva, Deborah L. McGuinness, Richard Fikes
Knowledge Systems Laboratory, Stanford University, Stanford, CA 94305, USA
Abstract
The Semantic Web is being designed to enable automated reasoners to be used as core components in a wide variety
of Web applications and services. In order for a client to accept and trust a result produced by perhaps an unfamiliar
Web service, the result needs to be accompanied by a justification that is understandable and usable by the client. In this
paper, we describe the proof markup language (PML), an interlingua representation for justifications of results
produced by Semantic Web services. We also introduce our Inference Web infrastructure that uses PML as the
foundation for providing explanations of Web services to end users. We additionally show how PML is critical for and
provides the foundation for hybrid reasoning where results are produced cooperatively by multiple reasoners. Our
contributions in this paper focus on technological foundations for capturing formal representations of term meaning
and justification descriptions thereby facilitating trust and reuse of answers from web agents.
[6]Rough sets: Some extensions
Zdzis?aw Pawlak, Andrzej Skowron *
Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warsaw, Poland
Abstract
In this article, we present some extensions of the rough set approach and we outline a challenge for the rough set based
research.
[7]Ontology-based distributed autonomous knowledge systems
ZbigniewW. Ra!sa,b,*, Agnieszka Dardzi!nskac
aDepartment of Computer Science, University of North Carolina, Charlotte, NC 28223, USA
b Polish Academy of Sciences, Institute of Computer Science, Ordona 21, 01-237 Warsaw, Poland
cDepartment of Mathematics, Bialystok University of Technology, Wiejska 45 A, 15-351 Bialystok, Poland
Abstract
Traditional query processing usually requires that users fully understand the database structure and content to issue a
query. Due to the complexity of the database applications and the variety of user needs, the so-called global queries are
introduced which traditional query answering systems cannot handle. Query posed to a database D is global if
minimum one of its attributes is missing in D while it occurs in other databases. Definitions of a missing attribute in D
can be extracted from other databases and shared with D: To handle semantics inconsistencies between the same
attributes used at different sites, task ontologies are used as a communication bridge between them. These
inconsistencies can be caused either by different granularity levels or by different interpretations of the same attribute.
As the final outcome of this research, a rough query answering system based on distributed data mining is presented.
[8]Learning ontologies from natural language texts
Mehrnoush Shamsfard*, Ahmad Abdollahzadeh Barforoush
Intelligent Systems Laboratory, Computer Engineering Department, Amir Kabir University of Technology,
Hafez ave., Tehran 15, Iran
Abstract
Research on ontology is becoming increasingly widespread in the computer science
community. The major problems in building ontologies are the bottleneck of knowledge
acquisition and time-consuming construction of various ontologies for various domains/
applications. Meanwhile moving toward automation of ontology construction is a
solution.
We proposed an automatic ontology building approach. In this approach, the system starts
from a small ontology kernel and constructs the ontology through text understanding
automatically. The kernel contains the primitive concepts, relations and operators to build an
ontology. The features of our proposed model are being domain/application independent,
building ontologies upon a small primary kernel, learning words, concepts, taxonomic and
non-taxonomic relations and axioms and applying a symbolic, hybrid ontology learning
approach consisting of logical, linguistic based, template driven and semantic analysis
methods.
Hasti is an ongoing project to implement and test the automatic ontology building
approach. It extracts lexical and ontological knowledge from Persian (Farsi) texts.
In this paper, at first, we will describe some ontology engineering problems, which
motivated our approach. In the next sections, after a brief description of Hasti, its features
and its architecture, we will discuss its components in detail. In each part, the learning
algorithms will be described. Then some experimental results will be discussed and at last, we
will have an overview of related works and will introduce a general framework to compare
ontology learning systems and will compare Hasti with related works according to the
framework.
[9]Grounding the OML metamodel in ontology
Andreas L. Opdahl a,Brian Henderson-Sellers b
a Department of Information Science,University of Bergen,Norway
Abstract
The paper analyses and evaluates the OPEN Modelling Language (OML) in terms of Bunge-Wand-Weber(BWW) model of information systems in order to:...
[10]How to structure and access XML documents with ontologies
Michael Erdmann *, Rudi Studer
Institut fur Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Universat Karlsruhe (TH), Englerstrasse 11,
D-76128 Karlsruhe, Germany
Abstract
The current hype on Extensible Mark-up Language (XML) produced hundreds of XML-based applications. Many
of them o?er document type de?nitions (DTDs) to structure actual XML documents. Access to these documents relies
on special purpose applications or on query languages that are closely tied to the document structure. Our approach
uses ontologies to derive canonical structures, i.e., DTDs, to access sets of distributed XML documents on a conceptual
level. We will show how the combination of conceptual modeling, inheritance, and inference mechanisms with the
popularity, simplicity, and ˉexibility of XML leads to applications providing a broad range of high-quality information.
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