This document summarizes a PhD student's research on generating natural language explanations of entailments in OWL ontologies to help non-specialists understand and debug ontologies. The research aims to identify common justification patterns and develop an approach to explaining justifications in an accessible way using techniques from proof presentations. A preliminary study identified the most frequent patterns in a corpus of ontologies. The research will further analyze justification patterns and test explanations' effectiveness through user studies.
Building an Ontology in Educational Domain Case Study for the University of P...IJRES Journal
The current web is based on HTML which cannot be demoralized by information retrieval techniques and therefore processing of information on the web is generally restricted to manual keyword searches which results in unrelated information retrieval, so the semantic web was founded to resolve this problem; furthermore, ontology is used to capture knowledge about any domain of interest with the goal of integrating the machine understandable data on the current human-readable web. Web Ontology Language (OWL) is a semantic markup language for sharing ontologies on the web. In this paper, the education domain and the development of a University Ontology using Protégé 4.1 Editor is considered. The University of Palestine was chosen as an example for the Ontology Development and the diverse aspects: super class and sub class hierarchy, creating a sub class, instances for classes illustration, query retrieval process using the Unified Process for Building the Ontology (UPON) technique.
A little more semantics goes a lot further! Getting more out of Linked Data ...Michel Dumontier
This tutorial will provide detailed instruction to create and make use of formalized ontologies from linked open data for advanced knowledge discovery including consistency checking and answering sophisticated questions.
Automated reasoning in OWL offers the tantalizing possibility to undertake advanced knowledge discovery including verifying the consistency of conceptual schemata in information systems, verifying data integrity and answering expressive queries over the conceptual schema and the data. Given that a large amount of structured knowledge is now available as linked data, the challenge is to formalize this knowledge iso that intended semantics become explicit and that the reasoning is efficient and scalable. While using the full expressiveness of OWL 2 yields ontologies that can be used for consistency verification, classification and query answering, use of less expressive OWL profiles enable efficient reasoning and support different application scenarios. In this tutorial,
- we describe how to generate OWL ontologies from linked data
- check consistency of knowledge
- automatically transform ontologies into OWL profiles
- use this knowledge in applications to integrate data and answer sophisticated questions across domains.
- expressive ontologies enables data integration, verifying consistency of knowledge and answering questions
- formalization of linked data will create new opportunities for knowledge discovery
- OWL 2 profiles support more efficient reasoning and query answering procedures
- recent technology facilitates the automatic conversion of OWL 2 ontologies into profiles
- OWL ontologies can dramatically extend the functionality of semantically-enabled web sites
Language Combinatorics: A Sentence Pattern Extraction Architecture Based on C...Waqas Tariq
A \"sentence pattern\" in modern Natural Language Processing is often considered as a subsequent string of words (n-grams). However, in many branches of linguistics, like Pragmatics or Corpus Linguistics, it has been noticed that simple n-gram patterns are not sufficient to reveal the whole sophistication of grammar patterns. We present a language independent architecture for extracting from sentences more sophisticated patterns than n-grams. In this architecture a \"sentence pattern\" is considered as n-element ordered combination of sentence elements. Experiments showed that the method extracts significantly more frequent patterns than the usual n-gram approach.
ONTOLOGICAL MODEL FOR CHARACTER RECOGNITION BASED ON SPATIAL RELATIONSsipij
In this paper, we present a set of spatial relations between concepts describing an ontological model for a
new process of character recognition. Our main idea is based on the construction of the domain ontology
modelling the Latin script. This ontology is composed by a set of concepts and a set of relations. The
concepts represent the graphemes extracted by segmenting the manipulated document and the relations are
of two types, is-a relations and spatial relations. In this paper we are interested by description of second
type of relations and their implementation by java code.
Semantic Rules Representation in Controlled Natural Language in FluentEditorCognitum
Abstract. The purpose of this paper is to present a way of representation of semantic rules (SWRL) in controlled natural language (English) in order to facilitate understanding the rules by humans interacting with a machine. The rule representation is implemented in FluentEditor – ontology editor with controlled natural language (CNL). The representation can be used in a lot of domains where people interact with machines and use specialized interfaces to define knowledge in a system (semantic knowledge base), e.g. representing medical knowledge and guidelines, procedures in crisis management or in management of any coordination processes. Such knowledge bases are able to support decision making in any discipline provided there is a knowledge stored in a proper semantic way.
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...IJwest
Ontology may be a conceptualization of a website into a human understandable, however machine-readable format consisting of entities, attributes, relationships and axioms. Ontologies formalize the intentional aspects of a site, whereas the denotative part is provided by a mental object that contains assertions about instances of concepts and relations. Semantic relation it might be potential to extract the whole family-tree of a outstanding personality employing a resource like Wikipedia. In a way, relations describe the linguistics relationships among the entities involve that is beneficial for a higher understanding of human language. The relation can be identified from the result of concept hierarchy extraction. The existing ontology learning process only produces the result of concept hierarchy extraction. It does not produce the semantic relation between the concepts. Here, we have to do the process of constructing the predicates and also first order logic formula. Here, also find the inference and learning weights using Markov Logic Network. To improve the relation of every input and also improve the relation between the contents we have to propose the concept of ARSRE. This method can find the frequent items between concepts and converting the extensibility of existing lightweight ontologies to formal one. The experimental results can produce the good extraction of semantic relations compared to state-of-art method.
Building an Ontology in Educational Domain Case Study for the University of P...IJRES Journal
The current web is based on HTML which cannot be demoralized by information retrieval techniques and therefore processing of information on the web is generally restricted to manual keyword searches which results in unrelated information retrieval, so the semantic web was founded to resolve this problem; furthermore, ontology is used to capture knowledge about any domain of interest with the goal of integrating the machine understandable data on the current human-readable web. Web Ontology Language (OWL) is a semantic markup language for sharing ontologies on the web. In this paper, the education domain and the development of a University Ontology using Protégé 4.1 Editor is considered. The University of Palestine was chosen as an example for the Ontology Development and the diverse aspects: super class and sub class hierarchy, creating a sub class, instances for classes illustration, query retrieval process using the Unified Process for Building the Ontology (UPON) technique.
A little more semantics goes a lot further! Getting more out of Linked Data ...Michel Dumontier
This tutorial will provide detailed instruction to create and make use of formalized ontologies from linked open data for advanced knowledge discovery including consistency checking and answering sophisticated questions.
Automated reasoning in OWL offers the tantalizing possibility to undertake advanced knowledge discovery including verifying the consistency of conceptual schemata in information systems, verifying data integrity and answering expressive queries over the conceptual schema and the data. Given that a large amount of structured knowledge is now available as linked data, the challenge is to formalize this knowledge iso that intended semantics become explicit and that the reasoning is efficient and scalable. While using the full expressiveness of OWL 2 yields ontologies that can be used for consistency verification, classification and query answering, use of less expressive OWL profiles enable efficient reasoning and support different application scenarios. In this tutorial,
- we describe how to generate OWL ontologies from linked data
- check consistency of knowledge
- automatically transform ontologies into OWL profiles
- use this knowledge in applications to integrate data and answer sophisticated questions across domains.
- expressive ontologies enables data integration, verifying consistency of knowledge and answering questions
- formalization of linked data will create new opportunities for knowledge discovery
- OWL 2 profiles support more efficient reasoning and query answering procedures
- recent technology facilitates the automatic conversion of OWL 2 ontologies into profiles
- OWL ontologies can dramatically extend the functionality of semantically-enabled web sites
Language Combinatorics: A Sentence Pattern Extraction Architecture Based on C...Waqas Tariq
A \"sentence pattern\" in modern Natural Language Processing is often considered as a subsequent string of words (n-grams). However, in many branches of linguistics, like Pragmatics or Corpus Linguistics, it has been noticed that simple n-gram patterns are not sufficient to reveal the whole sophistication of grammar patterns. We present a language independent architecture for extracting from sentences more sophisticated patterns than n-grams. In this architecture a \"sentence pattern\" is considered as n-element ordered combination of sentence elements. Experiments showed that the method extracts significantly more frequent patterns than the usual n-gram approach.
ONTOLOGICAL MODEL FOR CHARACTER RECOGNITION BASED ON SPATIAL RELATIONSsipij
In this paper, we present a set of spatial relations between concepts describing an ontological model for a
new process of character recognition. Our main idea is based on the construction of the domain ontology
modelling the Latin script. This ontology is composed by a set of concepts and a set of relations. The
concepts represent the graphemes extracted by segmenting the manipulated document and the relations are
of two types, is-a relations and spatial relations. In this paper we are interested by description of second
type of relations and their implementation by java code.
Semantic Rules Representation in Controlled Natural Language in FluentEditorCognitum
Abstract. The purpose of this paper is to present a way of representation of semantic rules (SWRL) in controlled natural language (English) in order to facilitate understanding the rules by humans interacting with a machine. The rule representation is implemented in FluentEditor – ontology editor with controlled natural language (CNL). The representation can be used in a lot of domains where people interact with machines and use specialized interfaces to define knowledge in a system (semantic knowledge base), e.g. representing medical knowledge and guidelines, procedures in crisis management or in management of any coordination processes. Such knowledge bases are able to support decision making in any discipline provided there is a knowledge stored in a proper semantic way.
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...IJwest
Ontology may be a conceptualization of a website into a human understandable, however machine-readable format consisting of entities, attributes, relationships and axioms. Ontologies formalize the intentional aspects of a site, whereas the denotative part is provided by a mental object that contains assertions about instances of concepts and relations. Semantic relation it might be potential to extract the whole family-tree of a outstanding personality employing a resource like Wikipedia. In a way, relations describe the linguistics relationships among the entities involve that is beneficial for a higher understanding of human language. The relation can be identified from the result of concept hierarchy extraction. The existing ontology learning process only produces the result of concept hierarchy extraction. It does not produce the semantic relation between the concepts. Here, we have to do the process of constructing the predicates and also first order logic formula. Here, also find the inference and learning weights using Markov Logic Network. To improve the relation of every input and also improve the relation between the contents we have to propose the concept of ARSRE. This method can find the frequent items between concepts and converting the extensibility of existing lightweight ontologies to formal one. The experimental results can produce the good extraction of semantic relations compared to state-of-art method.
it's our presentation during the third international conference of information systems and technologies ICIST 2013 held at Tangier, Morocco in which we propose a new approach for human assessment of ontologies using an online questionnaire.
The increased potential of the ontologies to reduce the human interference has wide range of applications. This paper identifies requirements for an ontology development platform to innovate artificially intelligent web. To facilitate this process, RDF and OWL have been developed as standard formats for the sharing and integration of data and knowledge. The knowledge in the form of rich conceptual schemas called ontologies. Based on the framework, an architectural paradigm is put forward in view of ontology engineering and development of ontology applications and a development portal designed to support ontology engineering, content authoring and application development with a view to maximal scalability in size and complexity of semantic knowledge and flexible reuse of ontology models and ontology application processes in a distributed and collaborative engineering environment.
A Natural Logic for Artificial Intelligence, and its Risks and Benefits gerogepatton
This paper is a multidisciplinary project proposal, submitted in the hopes that it may garner enough interest to launch it with members of the AI research community along with linguists
and philosophers of mind and language interested in constructing a semantics for a natural logic for AI. The paper outlines some of the major hurdles in the way of “semantics-driven” natural language processing based on standard predicate logic and sketches out the steps to be
taken toward a “natural logic”, a semantic system explicitly defined on a well-regimented (but indefinitely expandable) fragment of a natural language that can, therefore, be “intelligently” processed by computers, using the semantic representations of the phrases of the fragment.
A Semi-Automatic Ontology Extension Method for Semantic Web ServicesIDES Editor
this paper provides a novel semi-automatic ontology
extension method for Semantic Web Services (SWS). This is
significant since ontology extension methods those existing
in literature mostly deal with semantic description of static
Web resources such as text documents. Hence, there is a need
for methods that can serve dynamic Web resources such as
SWS. The developed method in this paper avoids redundancy
and respects consistency so as to assure high quality of the
resulting shared ontologies.
ONTOLOGY SERVICE CENTER: A DATAHUB FOR ONTOLOGY APPLICATION dannyijwest
With the growth of data-oriented research in humanities, a large number of research datasets have been
created and published through web services. However, how to discover, integrate and reuse these distributed
heterogeneous research datasets is a challenging task. Ontology is the soul between series digital humanities
resources, which provides a good way for people to discover and understand these datasets. With the release
of more and more linked open data and knowledge bases, a large number of ontologies have been produced
at the same time
International Journal of Engineering and Science Invention (IJESI) inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Dictionary based concept mining an application for turkishcsandit
In this study, a dictionary-based method is used to extract expressive concepts from documents.
So far, there have been many studies concerning concept mining in English, but this area of
study for Turkish, an agglutinative language, is still immature. We used dictionary instead of
WordNet, a lexical database grouping words into synsets that is widely used for concept
extraction. The dictionaries are rarely used in the domain of concept mining, but taking into
account that dictionary entries have synonyms, hypernyms, hyponyms and other relationships in
their meaning texts, the success rate has been high for determining concepts. This concept
extraction method is implemented on documents, that are collected from different corpora.
A FRAMEWORK FOR BUILDING A MULTILINGUAL INDUSTRIAL ONTOLOGY: METHODOLOGY AND ...IJwest
As Web 3.0 is blooming, ontologies augment semantic Web with semi–structured knowledge. Industrial
ontologies can help in improving online commercial communication and marketing. In addition,
conceptualizing the enterprise knowledge can improve information retrieval for industrial applications.
Having ontologies combine multiple languages can help in delivering the knowledge to a broad sector of
Internet users. In addition, multi-lingual ontologies can also help in commercial transactions. This
research paper provides a framework model for building industrial multilingual ontologies which include
Corpus Determination, Filtering, Analysis, Ontology Building, and Ontology Evaluation. It also addresses
factors to be considered when modeling multilingual ontologies. A case study for building a bilingual
English-Arabic ontology for smart phones is presented. The ontology was illustrated using an ontology
editor and visualization tool. The built ontology consists of 67 classes and 18 instances presented in both
Arabic and English. In addition, applications for using the ontology are presented. Future research
directions for the built industrial ontology are presented.
Concept hierarchy is the backbone of ontology, and the concept hierarchy acquisition has been a hot topic in the field of ontology learning. this paper proposes a hyponymy extraction method of domain ontology concept based on cascaded conditional random field(CCRFs) and hierarchy clustering. It takes free text as extracting object, adopts CCRFs identifying the domain concepts. First the low layer of CCRFs is used to identify simple domain concept, then the results are sent to the high layer, in which the nesting concepts are recognized. Next we adopt hierarchy clustering to identify the hyponymy relation between domain ontology concepts. The experimental results demonstrate the proposed method is efficient.
Data integration is a perennial challenge facing large-scale data scientists. Bio-ontologies are useful in this endeavour as sources of synonyms and also for rules-based fuzzy integration pipelines.
Hướng dẫn tải và cài đặt revit structure 2015, revit architecture 2015 học revit tại http://rdsic.edu.vn/
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revit là gì
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tự học revit
tự học revit architecture 2015
it's our presentation during the third international conference of information systems and technologies ICIST 2013 held at Tangier, Morocco in which we propose a new approach for human assessment of ontologies using an online questionnaire.
The increased potential of the ontologies to reduce the human interference has wide range of applications. This paper identifies requirements for an ontology development platform to innovate artificially intelligent web. To facilitate this process, RDF and OWL have been developed as standard formats for the sharing and integration of data and knowledge. The knowledge in the form of rich conceptual schemas called ontologies. Based on the framework, an architectural paradigm is put forward in view of ontology engineering and development of ontology applications and a development portal designed to support ontology engineering, content authoring and application development with a view to maximal scalability in size and complexity of semantic knowledge and flexible reuse of ontology models and ontology application processes in a distributed and collaborative engineering environment.
A Natural Logic for Artificial Intelligence, and its Risks and Benefits gerogepatton
This paper is a multidisciplinary project proposal, submitted in the hopes that it may garner enough interest to launch it with members of the AI research community along with linguists
and philosophers of mind and language interested in constructing a semantics for a natural logic for AI. The paper outlines some of the major hurdles in the way of “semantics-driven” natural language processing based on standard predicate logic and sketches out the steps to be
taken toward a “natural logic”, a semantic system explicitly defined on a well-regimented (but indefinitely expandable) fragment of a natural language that can, therefore, be “intelligently” processed by computers, using the semantic representations of the phrases of the fragment.
A Semi-Automatic Ontology Extension Method for Semantic Web ServicesIDES Editor
this paper provides a novel semi-automatic ontology
extension method for Semantic Web Services (SWS). This is
significant since ontology extension methods those existing
in literature mostly deal with semantic description of static
Web resources such as text documents. Hence, there is a need
for methods that can serve dynamic Web resources such as
SWS. The developed method in this paper avoids redundancy
and respects consistency so as to assure high quality of the
resulting shared ontologies.
ONTOLOGY SERVICE CENTER: A DATAHUB FOR ONTOLOGY APPLICATION dannyijwest
With the growth of data-oriented research in humanities, a large number of research datasets have been
created and published through web services. However, how to discover, integrate and reuse these distributed
heterogeneous research datasets is a challenging task. Ontology is the soul between series digital humanities
resources, which provides a good way for people to discover and understand these datasets. With the release
of more and more linked open data and knowledge bases, a large number of ontologies have been produced
at the same time
International Journal of Engineering and Science Invention (IJESI) inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Dictionary based concept mining an application for turkishcsandit
In this study, a dictionary-based method is used to extract expressive concepts from documents.
So far, there have been many studies concerning concept mining in English, but this area of
study for Turkish, an agglutinative language, is still immature. We used dictionary instead of
WordNet, a lexical database grouping words into synsets that is widely used for concept
extraction. The dictionaries are rarely used in the domain of concept mining, but taking into
account that dictionary entries have synonyms, hypernyms, hyponyms and other relationships in
their meaning texts, the success rate has been high for determining concepts. This concept
extraction method is implemented on documents, that are collected from different corpora.
A FRAMEWORK FOR BUILDING A MULTILINGUAL INDUSTRIAL ONTOLOGY: METHODOLOGY AND ...IJwest
As Web 3.0 is blooming, ontologies augment semantic Web with semi–structured knowledge. Industrial
ontologies can help in improving online commercial communication and marketing. In addition,
conceptualizing the enterprise knowledge can improve information retrieval for industrial applications.
Having ontologies combine multiple languages can help in delivering the knowledge to a broad sector of
Internet users. In addition, multi-lingual ontologies can also help in commercial transactions. This
research paper provides a framework model for building industrial multilingual ontologies which include
Corpus Determination, Filtering, Analysis, Ontology Building, and Ontology Evaluation. It also addresses
factors to be considered when modeling multilingual ontologies. A case study for building a bilingual
English-Arabic ontology for smart phones is presented. The ontology was illustrated using an ontology
editor and visualization tool. The built ontology consists of 67 classes and 18 instances presented in both
Arabic and English. In addition, applications for using the ontology are presented. Future research
directions for the built industrial ontology are presented.
Concept hierarchy is the backbone of ontology, and the concept hierarchy acquisition has been a hot topic in the field of ontology learning. this paper proposes a hyponymy extraction method of domain ontology concept based on cascaded conditional random field(CCRFs) and hierarchy clustering. It takes free text as extracting object, adopts CCRFs identifying the domain concepts. First the low layer of CCRFs is used to identify simple domain concept, then the results are sent to the high layer, in which the nesting concepts are recognized. Next we adopt hierarchy clustering to identify the hyponymy relation between domain ontology concepts. The experimental results demonstrate the proposed method is efficient.
Data integration is a perennial challenge facing large-scale data scientists. Bio-ontologies are useful in this endeavour as sources of synonyms and also for rules-based fuzzy integration pipelines.
Hướng dẫn tải và cài đặt revit structure 2015, revit architecture 2015 học revit tại http://rdsic.edu.vn/
hoc revit
học revit
học revit
hoc revit 2014
học revit 2014
hoc revit 2015
hoc revit architecture tai ha noi
học revit cơ bản
hoc revit ha noi
hoc revit mep
học revit mep
hoc revit mep 2014
hoc revit mep o ha noi
hoc revit mep o ha noi
học revit ở đâu
hoc revit o tphcm
học revit online
học revit structure ở đâu
học revit structure ở đâu
học revit structure ở đâu là tốt nhất
lop hoc revit
lớp học revit mep tại hà nội
phương pháp học revit
revit là gì
tai lieu hoc revit
Tài liệu revit
trung tam day revit
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tự học revit architecture 2015
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Building Information Modeling is a design and documentation methodology based on coordinated, high quality information. It enables design and construction teams to create and manage information about a building project consistently and reliably across the scope of the project. The information is stored in a single building model. This ensures that information is coordinated, consistent, and complete.
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A Comparative Study Ontology Building Tools for Semantic Web Applications IJwest
Ontologies have recently received popularity in the area of knowledge management and knowledge sharing,
especially after the evolution of the Semantic Web and its supporting technologies. An ontology defines the terms
and concepts (meaning) used to describe and represent an area of knowledge.The aim of this paper is to identify all
possible existing ontologies and ontology management tools (Protégé 3.4, Apollo, IsaViz & SWOOP) that are freely
available and review them in terms of: a) interoperability, b) openness, c) easiness to update and maintain, d)
market status and penetration. The results of the review in ontologies are analyzed for each application area, such
as transport, tourism, personal services, health and social services, natural languages and other HCI-related
domains. Ontology Building/Management Tools are used by different groups of people for performing diverse tasks.
Although each tool provides different functionalities, most of the users just use only one, because they are not able
to interchange their ontologies from one tool to another. In addition, we considered the compatibility of different
ontologies with different development and management tools. The paper is also concerns the detection of
commonalities and differences between the examined ontologies, both on the same domain (application area) and
among different domains.
A Comparative Study Ontology Building Tools for Semantic Web Applications dannyijwest
Ontologies have recently received popularity in the area of knowledge management and knowledge sharing, especially after the evolution of the Semantic Web and its supporting technologies. An ontology defines the terms and concepts (meaning) used to describe and represent an area of knowledge.The aim of this paper is to identify all possible existing ontologies and ontology management tools (Protégé 3.4, Apollo, IsaViz & SWOOP) that are freely available and review them in terms of: a) interoperability, b) openness, c) easiness to update and maintain, d) market status and penetration. The results of the review in ontologies are analyzed for each application area, such as transport, tourism, personal services, health and social services, natural languages and other HCI-related domains. Ontology Building/Management Tools are used by different groups of people for performing diverse tasks. Although each tool provides different functionalities, most of the users just use only one, because they are not able to interchange their ontologies from one tool to another. In addition, we considered the compatibility of different ontologies with different development and management tools. The paper is also concerns the detection of commonalities and differences between the examined ontologies, both on the same domain (application area) and among different domains.
A Comparative Study of Ontology building Tools in Semantic Web Applications dannyijwest
Ontologies have recently received popularity in the area of knowledge management and knowledge sharing,
especially after the evolution of the Semantic Web and its supporting technologies. An ontology defines the terms
and concepts (meaning) used to describe and represent an area of knowledge.The aim of this paper is to identify all
possible existing ontologies and ontology management tools (Protégé 3.4, Apollo, IsaViz & SWOOP) that are freely
available and review them in terms of: a) interoperability, b) openness, c) easiness to update and maintain, d)
market status and penetration. The results of the review in ontologies are analyzed for each application area, such
as transport, tourism, personal services, health and social services, natural languages and other HCI-related
domains. Ontology Building/Management Tools are used by different groups of people for performing diverse tasks.
Although each tool provides different functionalities, most of the users just use only one, because they are not able
to interchange their ontologies from one tool to another. In addition, we considered the compatibility of different
ontologies with different development and management tools. The paper is also concerns the detection of
commonalities and differences between the examined ontologies, both on the same domain (application area) and
among different domains.
LOANONT-A RULE BASED ONTOLOGY FOR PERSONAL LOAN ELIGIBILITY EVALUATIONIJwest
In recent years, significant attention has been given to understand and implement banking solutions. The
global competitive business environment and advancement in Information Technology and in particular
internet technologies has facilitated the carrying out of banking activities outside the brick and mortar
premise of the banks. Credit availing schemes are the core of the banking industry. Many agencies are
working on it so as to make this facility hassle free for the customers and also to minimize the losses
incurred by the banks in the form of bad debts. The challenge has been, and still is, to recognize,
communicate and steadily improvise the banking solutions. The internet technologies are a potential
candidates to overcome these challenges. The paper describes LoanOnt Ontology with the associated
implementation toolset for creating an interoperable and sustainable personal loan calculation solution
which would provide an intercommunication platform to facilitate integration and interoperation of
information across interacting applications in banking scenarios.
Association Rule Mining Based Extraction of Semantic Relations Using Markov ...dannyijwest
Ontology may be a conceptualization of a website into a human understandable, however machine-
readable format consisting of entities, attributes, relationships and axioms. Ontologies formalize the
intentional aspects of a site, whereas the denotative part is provided by a mental object that contains
assertions about instances of concepts and relations. Semantic relation it might be potential to extract the
whole family-tree of a outstanding personality employing a resource like Wikipedia. In a way, relations
describe the linguistics relationships among the entities involve that is beneficial for a higher
understanding of human language. The relation can be identified from the result of concept hierarchy
extraction. The existing ontology learning process only produces the result of concept hierarchy extraction.
It does not produce the semantic relation between the concepts. Here, we have to do the process of
constructing the predicates and also first order logic formula. Here, also find the inference and learning
weights using Markov Logic Network. To improve the relation of every input and also improve the relation
between the contents we have to propose the concept of ARSRE.
Swoogle: Showcasing the Significance of Semantic SearchIDES Editor
The World Wide Web hosts vast repositories of
information. The retrieval of required information from the
Internet is a great challenge since computer applications
understand only the structure and layout of web pages and
they do not have access to their intended meaning. Semantic
web is an effort to enhance the Internet, so that computers
can process the information presented on WWW, interpret
and communicate with it, to help humans find required
essential knowledge. Application of Ontology is the
predominant approach helping the evolution of the Semantic
web. The aim of our work is to illustrate how Swoogle, a
semantic search engine, helps make computer and WWW
interoperable and more intelligent. In this paper, we discuss
issues related to traditional and semantic web searching. We
outline how an understanding of the semantics of the search
terms can be used to provide better results. The experimental
results establish that semantic search provides more focused
results than the traditional search.
INFERENCE BASED INTERPRETATION OF KEYWORD QUERIES FOR OWL ONTOLOGYIJwest
Most of the systems presented to date deals with RDF format so they are limited in actually addressing the
knowledge base features from the ontology based on OWL semantics. Now, there is a need that actual OWL
features i.e. rules and axioms must be addressed to give precise answers to the user queries. This paper
presents an interface to OWL ontology which also considers axioms and restrictions that can result in
inferring results in understanding user queries and in selecting appropriate SPARQL queries for getting
better interpretation and answers.
This article is a continuation of our researches on the
competency-based approach (CBA). It presents the ways that can
facilitate and generalize the understanding of CBA, its adoption
and its implementation in the educational system of Morocco.
The work described in this paper aims of the final stages of an
ontology’s development, when consensus is reached. More
precisely, the stage of operationalization: the process that allows
the transforming from the conceptual representation of
knowledge in an ontology regardless of use, to one operational
representation appropriate to its use. This article gives an
overview of the constraints that characterize this stage and
opportunities that can be offered by the ontology’s
implementation. It outlines a functional draft of a learning
platform architecture based on CBA, in order to guide the
choices made in the operationalization phase of CBA ontology.
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formatted in OWL document containing document sentence relevance for sentence retrieval.
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Increase in number of ontologies on Semantic Web and endorsement of OWL as language of discourse for
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Semantic Web. In this paper we present methods adopted for extraction and integration of concepts across
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Building Quranic stories ontology using MappingMaster domain-specific language IJECEIAES
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IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
USING RELATIONAL MODEL TO STORE OWL ONTOLOGIES AND FACTScsandit
The storing and the processing of OWL instances are important subjects in database modeling.
Many research works have focused on the way of managing OWL instances efficiently. Some
systems store and manage OWL instances using relational models to ensure their persistence.
Nevertheless, several approaches keep only RDF triplets as instances in relational tables
explicitly, and the manner of structuring instances as graph and keeping links between concepts
is not taken into account. In this paper, we propose an architecture that permits relational
tables behave as an OWL model by adapting relational tables to OWL instances and an OWL
hierarchy structure. Therefore, two kinds of tables are used: facts or instances relational tables.
The tables hold instances and the OWL table holds a specification of how the concepts are
structured. Instances tables should conform to OWLtable to be valid. A mechanism of
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The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
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Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
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http://sandymillin.wordpress.com/iateflwebinar2024
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1. 2010 CRC PhD Student Conference
Generating Accessible Natural Language Explanations for OWL
Ontologies
Tu Anh Nguyen
t.nguyen@open.ac.uk
Supervisors Richard Power
Paul Piwek
Sandra Williams
Department/Institute Computing Department
Status Full-time
Probation Viva Before
Starting date October 2009
Introduction
This research aims to develop a computational approach to generating accessible natural
language explanations for entailments in OWL ontologies. The purpose of it is to support
non-specialists, people who are not expert in description logic and formal ontology lan-
guages, in understanding why an inference or an inconsistency follows from an ontology.
This would help to further improve the ability of users to successfully debug, diagnose and
repair their ontologies. The research is linked to the Semantic Web Authoring Tool (SWAT)
project, the on-going project aiming to provide a natural language interface for ordinary
users to encode knowledge on the semantic web. The research questions are:
• Do justifications for entailments in OWL ontologies conform to a relatively small
number of common abstract patterns for which we could generalise the problem to
generating explanations by patterns?
• For a certain entailment and its justification, how to produce an explanation in natural
language that is accessible for non-specialists?
An ontology is a formal, explicit specification of a shared conceptualisation [6]. An ontology
language is a formal language used to encode ontologies. The Web Ontology Language,
OWL [8], is a widely used description logic based ontology language. Since OWL became
a W3C standard, there has been a remarkable increase in the number of people trying to
build and use OWL ontologies. Editing environments such as Prot´g´ [15] and Swoop [13]
e e
were developed in order to support users with editing and creating OWL ontologies.
As ontologies have begun to be widely used in real world applications and more expressive
ontologies have been required, there is a significant demand for editing environments that
provide more sophisticated editing and browsing services for debugging and repairing. In
addition to being able to perform standard description logic reasoning services namely sat-
isfiability checking and subsumption testing, description logic reasoners such as FaCT++
[22] and Pellet [20] can compute entailments (e.g., inferences) to improve the users com-
prehension about their ontologies. However, without providing some kind of explanation,
it can be very difficult for users to figure out why entailments are derived from ontologies.
The generation of justifications for entailments has proven enormously helpful for identi-
fying and correcting mistakes or errors in ontologies. Kalyanpur and colleagues defined a
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2. 2010 CRC PhD Student Conference
justification for an entailment of an ontology as the precise subset of logical axioms from
the ontology that are responsible for the entailment to hold [12]. Furthermore, he presented
a user study showing that the availability of justifications had a remarkable positive impact
on the ability of users to debug and repair their ontologies [11]. Justifications have also
been recently used for debugging very large ontologies such as SNOMED [1], which size is
too large to be able to debug and repair manually.
There are several recent studies into capturing justifications for entailments in OWL ontolo-
gies [12, 21, 9]. Nevertheless, OWL is a semantic markup language based on RDF and XML,
languages that are oriented toward machine processability rather than human readability.
Moreover, while a justification gathers together the axioms, or premises, sufficient for an
entailment to hold, it is left up to the reader to work out how these premises interplay with
each other to give rise to the entailment in question. Therefore, many users may struggle
to understand how a justification supports an entailment since they are either unfamiliar
with OWL syntax and semantics, or lack of knowledge about the logic underpinning the
ontology. In other words, the ability of users to work out how an entailment arises from a
justification currently depends on their understanding of OWL and description logic.
In recent years, the development of ontologies has been moving from “the realm of artificial
intelligence laboratories to the desktops of domain experts”, who have insightful knowledge
of some domain but no expertise in description logic and formal ontology languages [14].
It is for this reason that the desire to open up OWL ontologies to a wide non-specialist
audience has emerged. Obviously, the wide access to OWL ontologies depends on the devel-
opment of editing environments that use some transparent medium; and natural language
(e.g., English, Italian) text is an appropriate choice since it can be easily comprehended by
the public without training. Rector and colleagues observed common problems that users
frequently encounter in understanding the logical meaning and inferences when working
with OWL-DL ontologies, and expressed the need for a “pedantic but explicit” paraphrase
language to help users grasp the accurate meaning of logical axioms in ontologies [18].
Several research groups have proposed interfaces to encode knowledge in semantics-based
Controlled Natural Languages (CNLs) [19, 4, 10]. These systems allow users to input sen-
tences conforming with a CNL then parse and tranform them into statements in formal
ontology languages. The SWAT project [16] introduces an alternative approach based on
Natural Language Generation. In SWAT, users specify the content of an ontology by “di-
rectly manipulating on a generated feedback text” rather than using text interpretation;
therefore, “editing ontologies on the level of meaning, not text” [17].
Obviously, the above mentioned interfaces are designed for use by non-specialists to build up
ontologies without having to work directly on formal languages and description logic. How-
ever, research on providing more advanced editing and browsing services on these interfaces
to support the debugging and repairing process has not been investigated yet. Despite the
usefulness of providing justifications in the form of sets of OWL axioms, understanding the
reasons why entailments or inconsistencies are drawn from ontologies is still a key problem
for non-specialists. Even for specialists, having a more user-friendly view of ontology with
accessible explanations can be very helpful. Thus, this project seeks to develop a compu-
tational approach to generating accessible natural language explanations for entailments in
OWL ontologies in order to assist users in debugging and repairing their ontologies.
Methodology
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3. 2010 CRC PhD Student Conference
The research approach is to identify common abstract patterns of justifications for entail-
ments in OWL ontologies. Having identified such patterns we will focus on generating
accessible explanations in natural languages for most frequently used patterns. A prelim-
inary study to work out the most common justification patterns has been carried out. A
corpus of eighteen real and published OWL ontologies of different expressivity has been
collected from the Manchester TONEs reposistory. In addition, the practical module devel-
oped by Matthew Horridge based on the research on finding all justifications for OWL-DL
ontologies [12, 7] has been used. Justifications are computed then analysed to work out the
most common patterns. Results from the study show that over the total 6772 justifications
collected, more than 70 percent of justifications belongs to the top 20 patterns. Study on
a larger and more general ontology corpus will be carried out in next steps. Moreover, a
user study is planned to investigate whether non-specialists perform better on a task when
reading accessible explanations rather than justifications in the form of OWL axioms.
The research on how to create explanations accessible for non-logicians is informed by studies
on proof presentations. In Natural Deduction [5], how a conclusion is derived from a set of
premises is represented as a series of intermediate statements linking from the premises to
the conclusion. While this approach makes it easy for users to understand how to derive
from one step to the next, it might cause difficulty to understand how those steps linked
together to form the overall picture of the proof. Structured derivations [2], a top-down
calculational proof format that allows inferences to be presented at different levels of detail,
seems to be an alternative approach for presenting proof. It was proposed by researchers
as a method for teaching rigorous mathematical reasoning [3]. Research on whether using
structured derivations would help to improve the accessibility of explanations as well as
where and how intermediate inferences should be added is being investigated.
Conclusion
Since the desire to open up OWL ontologies to a wide non-specialist audience has emerged,
several research groups have proposed interfaces to encode knowledge in semantics-based
CNLs. However, research on providing debugging and repairing services on these inter-
faces has not been investigated yet. Thus, this research seeks to develope a computational
approach to generating accessible explanations to help users in understanding why an entail-
ment follows from a justification. Research work includes identifying common abstract jus-
tification patterns and studying into generating explanations accessible for non-specialists.
References
[1] F. Baader and B. Suntisrivaraporn. Debugging SNOMED CT Using Axiom Pinpointing
in the Description Logic EL+. In KR-MED, 2008.
[2] R. Back, J. Grundy, , and J. von Wright. Structured Calculational Proof. Technical
report, The Australian National University, 1996.
[3] R.-J. Back and J. von Wright. A Method for Teaching Rigorous Mathematical Rea-
soning. In ICTMT4, 1999.
[4] A. Bernstein and E. Kaufmann. GINO - A Guided Input Natural Language Ontology
Editor. In ISWC, 2006.
Page 67 of 125
4. 2010 CRC PhD Student Conference
[5] G. Gentzen. Untersuchungen uber das logische Schließen. II. Mathematische Zeitschrift,
¨
39:405–431, 1935.
[6] T. R. Gruber. A translation approach to portable ontology specifications. Knowledge
Acquisition, 5:199–220, 1993.
[7] M. Horridge, B. Parsia, and U. Sattler. Laconic and Precise Justifications in OWL. In
ISWC, pages 323–338, 2008.
[8] I. Horrocks, P. F. Patel-Schneider, and F. van Harmelen. From SROIQ and RDF to
OWL: The Making of a Web Ontology Language. J. Web Semantics, 1:7–26, 2003.
[9] Q. Ji, G. Qi, and P. Haase. A Relevance-Directed Algorithm for Finding Justifications
of DL Entailments. In ASWC, pages 306–320, 2009.
[10] K. Kaljurand and N. E. Fuchs. Verbalizing OWL in Attempto Controlled English. In
OWLED, 2007.
[11] A. Kalyanpur. Debugging and repair of OWL ontologies. PhD thesis, University of
Maryland, 2006.
[12] A. Kalyanpur, B. Parsia, M. Horridge, and E. Sirin. Finding All Justifications of OWL
DL Entailments. In ISWC, 2007.
[13] A. Kalyanpur, B. Parsia, E. Sirin, B. Cuenca-Grau, and J. A. Hendler. Swoop: A Web
Ontology Editing Browser. Journal of Web Semantics, 4:144–153, 2006.
[14] N. F. Noy and D. L. McGuinness. Ontology Development 101: A Guide to Creating
Your First Ontology. Technical report, Stanford University, 2001.
[15] N. F. Noy, M. Sintek, S. Decker, M. Crub´zy, R. W. Fergerson, and M. A. Musen.
e
Creating Semantic Web Contents with Prot´g´-2000. IEEE Intell. Syst., 16:60–71,
e e
2001.
[16] R. Power. Towards a generation-based semantic web authoring tool. In ENLG, pages
9–15, 2009.
[17] R. Power, R. Stevens, D. Scott, and A. Rector. Editing OWL through generated CNL.
In CNL, 2009.
[18] A. Rector, N. Drummond, M. Horridge, J. Rogers, H. Knublauch, R. Stevens, H. Wang,
and C. Wroe. OWL Pizzas: Practical Experience of Teaching OWL-DL: Common
Errors & Common Patterns. In EKAW, 2004.
[19] R. Schwitter and M. Tilbrook. Controlled Natural Language meets the Semantic Web.
In ALTW, pages 55–62, 2004.
[20] E. Sirin, B. Parsia, B. C. Grau, A. Kalyanpur, and Y. Katz. Pellet: A practical
OWL-DL reasoner. Journal of Web Semantics, 5:51–53, 2007.
[21] B. Suntisrivaraporn, G. Qi, Q. Ji, and P. Haase. A Modularization-based Approach to
Finding All Justifications for OWL DL Entailments. In ASWC, pages 1–15, 2008.
[22] D. Tsarkov and I. Horrocks. FaCT++ Description Logic Reasoner: System Description.
In IJCAR, volume 4130, pages 292–297, 2006.
Page 68 of 125