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Showing papers on "Upper ontology published in 2018"


Journal ArticleDOI
TL;DR: In this article, the authors discuss ontology-based information retrieval approaches and techniques by taking into consideration the aspects of ontology modelling, processing and the translation of ontological knowledge into database search requests.

143 citations


Journal ArticleDOI
01 Jan 2018
TL;DR: QAPD, an ontology-based QA system applied to the physics domain, which integrates natural language processing, ontologies and information retrieval technologies to provide informative information for users, is presented and inferring schema mapping method is proposed, which uses the combination of semantic and syntactic information, and attribute-based inference to transform users’ questions into ontological knowledge base query.
Abstract: The tremendous development in information technology led to an explosion of data and motivated the need for powerful yet efficient strategies for knowledge discovery. Question answering (QA) systems made it possible to ask questions and retrieve answers using natural language queries. In ontology-based QA system, the knowledge-based data, where the answers are sought, have a structured organization. The question-answer retrieval of ontology knowledge base provides a convenient way to obtain knowledge for use. In this paper, QAPD, an ontology-based QA system applied to the physics domain, which integrates natural language processing, ontologies and information retrieval technologies to provide informative information for users, is presented. This system allows users to retrieve information from formal ontologies using input queries formulated in natural language. We proposed inferring schema mapping method, which uses the combination of semantic and syntactic information, and attribute-based inference to transform users' questions into ontological knowledge base query. In addition, a novel domain ontology for physics domain, called EAEONT, is presented. Relevant standards and regulations have been utilized extensively during the ontology building process. The original characteristic of system is the strategy used to fill the gap between users' expressiveness and formal knowledge representation. This system has been developed and tested on the English language and using an ontology modeling the physics domain. The performance level achieved enables the use of the system in real environments.

41 citations


Book ChapterDOI
01 Jan 2018
TL;DR: An automatic topic ontology construction process for better topic classification is developed and a corpus based novel approach to enrich the set of categories in the ODP by automatically identifying concepts and their associated semantic relationships based on external knowledge from Wikipedia and WordNet is presented.
Abstract: The rapid growth of web technologies had created a huge amount of information that is available as web resources on Internet. Authors develop an automatic topic ontology construction process for better topic classification and present a corpus based novel approach to enrich the set of categories in the ODP by automatically identifying concepts and their associated semantic relationships based on external knowledge from Wikipedia and WordNet. The topic ontology construction process relies on concept acquisition and semantic relation extraction. Initially, a topic mapping algorithm is developed to acquire the concepts from Wikipedia based on semantic relations. A semantic similarity clustering algorithm is used to compute similarity to group the set of similar concepts. The semantic relation extraction algorithm derives associated semantic relations between the set of extracted topics from the lexical patterns in WordNet. The performance of the proposed topic ontology is evaluated for the classification of web documents and obtained results depict the improved performance over ODP.

26 citations


Journal ArticleDOI
TL;DR: The feasibility of ontology-driven automation of web service development that is to be a core element in the deployment of heterogeneous district-wide energy management software is assessed.

22 citations


Posted Content
TL;DR: The Information Flow Framework (IFF) as discussed by the authors is a descriptive category metatheory currently under development, which is being offered as the structural aspect of the Standard Upper Ontology (SUO).
Abstract: The Information Flow Framework (IFF) is a descriptive category metatheory currently under development, which is being offered as the structural aspect of the Standard Upper Ontology (SUO). The architecture of the IFF is composed of metalevels, namespaces and meta-ontologies. The main application of the IFF is institutional: the notion of institutions and their morphisms are being axiomatized in the upper metalevels of the IFF, and the lower metalevel of the IFF has axiomatized various institutions in which semantic integration has a natural expression as the colimit of theories.

19 citations


Posted Content
TL;DR: It is concluded that manually classifying domain entities under upper ontology classes is indeed very difficult to do correctly and it is necessary to improve the methodological framework surrounding the manual integration of domain and upper ontologies.
Abstract: Classifying entities in domain ontologies under upper ontology classes is a recommended task in ontology engineering to facilitate semantic interoperability and modelling consistency. Integrating upper ontologies this way is difficult and, despite emerging automated methods, remains a largely manual task. Little is known about how well experts perform at upper ontology integration. To develop methodological and tool support, we first need to understand how well experts do this task. We designed a study to measure the performance of human experts at manually classifying classes in a general knowledge domain ontology with entities in the Basic Formal Ontology (BFO), an upper ontology used widely in the biomedical domain. We conclude that manually classifying domain entities under upper ontology classes is indeed very difficult to do correctly. Given the importance of the task and the high degree of inconsistent classifications we encountered, we further conclude that it is necessary to improve the methodological framework surrounding the manual integration of domain and upper ontologies.

14 citations


Dissertation
24 Sep 2018
TL;DR: L’ontologie resultante est adoptee dans une approche homogene a base des ontologies pour formaliser the liste des regles juridiques du code penal en utilisant le langage logique SWRL.
Abstract: This thesis analyses the problem of building well-founded domain ontologies for reasoning and decision support purposes. Specifically, it discusses the building of legal ontologies for rule-based reasoning. In fact, building well-founded legal domain ontologies is considered as a difficult and complex process due to the complexity of the legal domain and the lack of methodologies. For this purpose, a novel middle-out approach called MIROCL is proposed. MIROCL tends to enhance the building process of well-founded domain ontologies by incorporating several support processes such as reuse, modularization, integration and learning. MIROCL is a novel modular middle-out approach for building well-founded domain ontologies. By applying the modularization process, a multi-layered modular architecture of the ontology is outlined. Thus, the intended ontology will be composed of four modules located at different abstraction levels. These modules are, from the most abstract to the most specific, UOM(Upper Ontology Module), COM(Core Ontology Module), DOM(Domain Ontology Module) and DSOM(Domain-Specific Ontology Module). The middle-out strategy is composed of two complementary strategies: top-down and bottom-up. The top-down tends to apply ODCM (Ontology-Driven Conceptual Modeling) and ontology reuse starting from the most abstract categories for building UOM and COM. Meanwhile, the bottom-up starts from textual resources, by applying ontology learning process, in order to extract the most specific categories for building DOM and DSOM. After building the different modules, an integration process is performed for composing the whole ontology. The MIROCL approach is applied in the criminal domain for modeling legal norms. A well-founded legal domain ontology called CriMOnto (Criminal Modular Ontology) is obtained. Therefore, CriMOnto has been used for modeling the procedural aspect of the legal norms by the integration with a logic rule language (SWRL). Finally, an hybrid approach is applied for building a rule-based system called CORBS. This system is grounded on CriMOnto and the set of formalized rules.

13 citations


Journal ArticleDOI
TL;DR: This work explores the use of a predictive statistical model to establish an alignment between two input ontologies and demonstrates how to integrate ontology partitioning and parallelism in the ontology matching process in order to make the statistical predictive model scalable to large ontological matching tasks.
Abstract: Ontologies have become a popular means of knowledge sharing and reuse. This has motivated development of large independent ontologies within the same or different domains with some overlapping information among them. In order to match such large ontologies, automatic matchers become an inevitable solution. This work explores the use of a predictive statistical model to establish an alignment between two input ontologies. We demonstrate how to integrate ontology partitioning and parallelism in the ontology matching process in order to make the statistical predictive model scalable to large ontology matching tasks. Unlike most ontology matching tools which establish 1:1 cardinality mappings, our statistical model generates one-to-many cardinality mappings.

13 citations


Journal ArticleDOI
TL;DR: A system architecture and prototypical implementation for an integrated data management of distributed databases based on a domain-specific ontology, which will enhance existing business analysis methods in the domain of IT benchmarking.
Abstract: In the domain of IT benchmarking (ITBM), a variety of data and information are collected. Although these data serve as the basis for business analyses, no unified semantic representation of such data yet exists. Consequently, data analysis across different distributed data sets and different benchmarks is almost impossible. This paper presents a system architecture and prototypical implementation for an integrated data management of distributed databases based on a domain-specific ontology. To preserve the semantic meaning of the data, the ITBM ontology is linked to data sources and functions as the central concept for database access. Thus, additional databases can be integrated by linking them to this domain-specific ontology and are directly available for further business analyses. Moreover, the web-based system supports the process of mapping ontology concepts to external databases by introducing a semi-automatic mapping recommender and by visualizing possible mapping candidates. The system al...

10 citations


Journal ArticleDOI
TL;DR: This paper analyzes the integration of XML-based standards with ontology to describe the meaning of the information and knowledge interchanged between trading partners to jointly execute business processes and defines the main components of an ontology development environment to support the entire ontology lifecycle.
Abstract: A collaborative B2B relationship implies jointly executing business processes. This relationship demands a complete access to available information and knowledge to support decision-making activities between trading partners. To support information interchange between enterprises in collaborative B2B ecommerce there are some XML-based standards technologies, like RosettaNet, ebXML and OAGIS. However, XML does not express semantics by itself. So, these standards only provide an infrastructure to support the information interchange. They are suitable to integrate information but not to support decision-making activities where a common understanding of the information is needed. In this paper we analyze the integration of these standards with ontology to describe the meaning of the information and knowledge interchanged between trading partners to jointly execute business processes. Furthermore, we define the main components of an ontology development environment to support the entire ontology lifecycle.

9 citations


Journal ArticleDOI
TL;DR: This work proposes an ontology for the domain of IT benchmarking, based on requirements mainly elicited from a domain analysis, which considers analyzing documents and interviews with representatives from Small- and Medium-Sized Enterprises and Information and Communications Technology companies over the last eight years.
Abstract: A domain-specific ontology for IT benchmarking has been developed to bridge the gap between a systematic characterization of IT services and their data-based valuation. Since information is generally collected during a benchmark exercise using questionnaires on a broad range of topics, such as employee costs, software licensing costs, and quantities of hardware, it is commonly stored as natural language text; thus, this information is stored in an intrinsically unstructured form. Although these data form the basis for identifying potentials for IT cost reductions, neither a uniform description of any measured parameters nor the relationship between such parameters exists. Hence, this work proposes an ontology for the domain of IT benchmarking, available at https://w3id.org/bmontology. The design of this ontology is based on requirements mainly elicited from a domain analysis, which considers analyzing documents and interviews with representatives from Small- and Medium-Sized Enterprises and Information and Communications Technology companies over the last eight years. The development of the ontology and its main concepts is described in detail (i.e., the conceptualization of benchmarking events, questionnaires, IT services, indicators and their values) together with its alignment with the DOLCE-UltraLite foundational ontology.

Journal ArticleDOI
TL;DR: This work has proposed an ontology DEMLOnto based on six basic emotions to help users to share existed information and is a useful first step in providing and formalizing the semantics of information representation.
Abstract: With the explosive growth of various social media applications, individuals and organizations are increasingly using their contents (e.g. reviews, forum discussions, blogs, micro-blogs, comments, and postings in social network sites) for decision-making. These contents are typical big data. Opinion mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help users to get a better decision. That is not an easy task, because it faces many problems, such as different context may make the meaning of the same word change variously, at the same time multilingual environment restricts the full use of the analysis results. Ontology provides knowledge about specific domains that are understandable by both the computers and developers. Building ontology is mainly a useful first step in providing and formalizing the semantics of information representation. We proposed an ontology DEMLOnto based on six basic emotions to help users to share existed information. The ont...


Journal ArticleDOI
TL;DR: In this article, a computational ontology for the Union of Concerned Scientists (UCS) Satellite Database (UCSSD) called the UCS Satellite Ontology (or UCSSO) is presented.
Abstract: This paper demonstrates the development of ontology for satellite databases. First, I create a computational ontology for the Union of Concerned Scientists (UCS) Satellite Database (UCSSD for short), called the UCS Satellite Ontology (or UCSSO). Second, in developing UCSSO I show that The Space Situational Awareness Ontology (SSAO) (Rovetto and Kelso 2016)--an existing space domain reference ontology--and related ontology work by the author (Rovetto 2015, 2016) can be used either (i) with a database-specific local ontology such as UCSSO, or (ii) in its stead. In case (i), local ontologies such as UCSSO can reuse SSAO terms, perform term mappings, or extend it. In case (ii), the author's orbital space ontology work, such as the SSAO, is usable by the UCSSD and organizations with other space object catalogs, as a reference ontology suite providing a common semantically-rich domain model. The SSAO, UCSSO, and the broader Orbital Space Environment Domain Ontology project is online at this http URL and GitHub. This ontology effort aims, in part, to provide accurate formal representations of the domain for various applications. Ontology engineering has the potential to facilitate the sharing and integration of satellite data from federated databases and sensors for safer spaceflight.

Book ChapterDOI
01 Jan 2018
TL;DR: OntoMaven as discussed by the authors adopts the Maven-based development methodology and adapts its concepts to knowledge engineering for Mavenbased ontology development and management of ontology artifacts in distributed ontology repositories.
Abstract: In collaborative agile ontology development projects support for modular reuse of ontologies from large existing remote repositories, ontology project life cycle management, and transitive dependency management are important needs. The Apache Maven approach has proven its success in distributed collaborative Software Engineering by its widespread adoption. The contribution of this paper is a new design artifact called OntoMaven. OntoMaven adopts the Maven-based development methodology and adapts its concepts to knowledge engineering for Maven-based ontology development and management of ontology artifacts in distributed ontology repositories.

Book ChapterDOI
01 Jan 2018
TL;DR: This paper is the first work that addresses the process of Arabic Semantic Relation Extraction from the Ontology learning perspective and reviews the conducted researches in both areas.
Abstract: Semantic relations are the building blocks of the Ontologies and any modern knowledge representation system. Extracting semantic relations from the text is one of the most significant and challenging phases in the Ontology learning process. It is essential in all Ontology learning phases starting from building the Ontology from scratch, down to populating and enriching the existing Ontologies. It is challenging, on the other hand, as it requires dealing with natural language text, which represents various challenges especially for syntactically ambiguous languages such as Arabic. In this paper, we present a comprehensive survey of Arabic Semantic Relation Extraction and Arabic Ontology learning research areas. We study Arabic Ontology learning in general while focusing on Arabic Semantic Relation Extraction particularly, as being the most significant, yet challenging task in the Ontology learning process. To the best of our knowledge, this is the first work that addresses the process of Arabic Semantic Relation Extraction from the Ontology learning perspective. We review the conducted researches in both areas. For each research the used technique is illustrated, the limitations and the positive aspects are clarified.

Proceedings Article
02 Sep 2018
TL;DR: This paper analyses existing modeling approaches and classify them according to some revelant characteristics of knowledge modeling, and presents transformation rules between ontology models in order to allow a powerful usage of ontologies in data management and knowledge.
Abstract: Ontologies are seen like the more relevant way to solve data understanding problem and to allow programs to perform meaningful operations on data in various domains. However, it appears that none of the proposed models is complete enough by itself to cover all aspects of knowledge applications. In this paper, we analyse existing modeling approaches and classify them according to some revelant characteristics of knowledge modeling we have identified. Finally, this paper present transformation rules between ontology models in order to get benefits of their strengths and to allow a powerful usage of ontologies in data management and knowledge

Proceedings ArticleDOI
18 Sep 2018
TL;DR: In this article, an extension of E-OntoUML, a language for modelling task ontologies, is suggested to describe methods for modeling task objectives, external event interference, pre/post conditions and task execution state modifications in order to guide future research.
Abstract: Different from domain ontologies, task ontologies must describe the knowledge from its structural and behavioural views, considering aspects as sequence of execution, conditional deviation, external expected and unexpected events interference, pre and post conditions, task granularity, agent participation, geographic localization, resource consummation, production and change. Although the use of conceptual models is well accepted to formally describe domain ontologies, there is little research about conceptual models for complex task ontologies. This paper describes the ongoing research on the Agriculture Operations Task Ontology (AGROPTO) where OntoUML is used to develop conceptual models to describe complex task’s aspects and possible modelling solutions based on Unified Foundation Ontology (UFO). An extension of the E-OntoUML, a language for modelling task ontologies, is suggested to describe methods for modelling task objectives, external event interference, pre/post conditions and task execution state modifications in order to guide future research.

Journal ArticleDOI
Ahmad Hawalah1
TL;DR: This paper will first extract and build an Arabic ontology from a publicly available directory, following which, this ontology will be enhanced with rich data from the Internet and a multi-disciplinary ontology that provides a hierarchical representation of topics in a conceptual way is constructed.
Abstract: Over recent years, the Internet has become people’s main source of information, with many databases and web pages being added and accessed every day. This continued growth in the amount of information available has led to frustration and difficulty for those attempting to find a specific piece of information. As such, many techniques are widely used to retrieve useful information and to mine valuable data; indeed, these techniques make it possible to discover hidden relations and patterns. Most of the above-mentioned techniques have been used primarily to process and analyse English text, but not Arabic text. Limited Arabic resources (e.g. datasets, databases, and ontologies), also make analysing and processing Arabic text a difficult task. As such, in this paper, we propose a framework for building an Arabic ontology from multiple resources. Thus, we will first extract and build an Arabic ontology from a publicly available directory, following which, we will enhance this ontology with rich data from the Internet. We will then use an Arabic online directory to construct a multi-disciplinary ontology that provides a hierarchical representation of topics in a conceptual way. Following this, we introduce an enhanced technique to enrich these ontologies with sufficient information and proper annotation for each concept. Finally, by using common information retrieval evaluation techniques, we confirm the viability of the proposed approach.

Journal ArticleDOI
TL;DR: This work describes a visual system for managing ontologies in the RDF formalism, providing a number of features for creating, updating and deleting elements and instances via a user-friendly graphical interface, along with a set of advanced operators that can be applied upon them.
Abstract: This work describes a visual system for managing ontologies in the RDF formalism, providing a number of features for creating, updating and deleting elements and instances via a user-friendly graphical interface, along with a set of advanced operators that can be applied upon them. These operators implement mechanisms for ontology instance matching and integration, ontology enrichment with semantically-related concepts, as well as question answering in natural language, with the purpose of discovering knowledge from the underlying ontologies. SEMANTO may display and manage RDF ontologies via SPARQL endpoints, including user-defined ontologies and subsets of Linked Open Data. SEMANTO has been experimented upon against ontological schema and instances derived from a knowledge model for learning management systems and from a learning application for online dispute resolution.

Proceedings Article
24 Mar 2018
TL;DR: This work investigates the use of quality metrics for Content ODP evaluation in terms of metrics applicability and validity, and discusses the general applicability of each metric considering its definition, ODP characteristics, and the defined goals of ODPs.
Abstract: Ontology Design Patterns (ODPs) provide best practice solutions for common or recurring ontology design problems. This work focuses on Content ODPs. These form small ontologies themselves and thus can be subject to ontology quality metrics in general. We investigate the use of such metrics for Content ODP evaluation in terms of metrics applicability and validity. The quality metrics used for this investigation are taken from existing work in the area of ontology quality evaluation. We discuss the general applicability to Content ODPs of each metric considering its definition, ODP characteristics, and the defined goals of ODPs. Metrics that revealed to be applicable are calculated for a random set of 10 Content ODPs from the ODP wiki-portal that was initiated by the NeOn-project. Interviews have been conducted for an explorative view into the correlation of quality metrics and evaluation by users.

Journal ArticleDOI
25 Oct 2018
TL;DR: The EOHD model demonstrates how to apply the event ontology to biographical sketches of a creator history to link event types and has great potential to be further expanded to specific events and entities through different types of history in a full set of historical documents.
Abstract: This study aims to explore a way of representing historical collections by examining the features of an event in historical documents and building an event-based ontology model.,To align with a domain-specific and upper ontology, the Basic Formal Ontology (BFO) model is adopted. Based on BFO, an event-based ontology for historical description (EOHD) is designed. To define events, event-related vocabularies are taken from the Library of Congress’ event types (2012). The three types of history and six kinds of changes are defined.,The EOHD model demonstrates how to apply the event ontology to biographical sketches of a creator history to link event types.,The EOHD model has great potential to be further expanded to specific events and entities through different types of history in a full set of historical documents.,The EOHD provides a framework for modeling and semantically reforming the relationships of historical documents, which can make historical collections more explicitly connected in Web environments.

Proceedings ArticleDOI
01 Nov 2018
TL;DR: The DUL Event, Situation, Description pattern is used to formalize reasoning techniques to convert between a robot’s beliefstate and its linguistic utterances, to equip robots with a reason-aloud ability.
Abstract: We propose the combination of a robotics ontology (KnowRob) with a linguistically motivated one (GUM) under the upper ontology DUL. We use the DUL Event, Situation, Description pattern to formalize reasoning techniques to convert between a robot’s beliefstate and its linguistic utterances. We plan to employ these techniques to equip robots with a reason-aloud ability, through which they can explain their actions as they perform them, in natural language, at a level of granularity appropriate to the user, their query and the context at hand.

Posted Content
TL;DR: In this paper, a link between probabilistic reasoning in Probabilistic Context Free Grammars (PCFG) and Multi Entity Bayesian Networks (MEBN) is established by proposing a formal description of PCFG driven by MEBN.
Abstract: Probabilistic context free grammars (PCFG) have been the core of the probabilistic reasoning based parsers for several years especially in the context of the NLP. Multi entity bayesian networks (MEBN) a First Order Logic probabilistic reasoning methodology is widely adopted and used method for uncertainty reasoning. Further upper ontology like Probabilistic Ontology Web Language (PR-OWL) built using MEBN takes care of probabilistic ontologies which model and capture the uncertainties inherent in the domain's semantic information. The paper attempts to establish a link between probabilistic reasoning in PCFG and MEBN by proposing a formal description of PCFG driven by MEBN leading to usage of PR-OWL modeled ontologies in PCFG parsers. Furthermore, the paper outlines an approach to resolve prepositional phrase (PP) attachment ambiguity using the proposed mapping between PCFG and MEBN.

01 Jan 2018
TL;DR: Semantic Annotator for Inkscape (SAI) is introduced, an authoring tool that allows for seamless addition of semantics to an SVG file supported by a given upper ontology in RDF format, improving the efficiency of authoring semantically-enhanced graphics.
Abstract: Semantically-enhanced graphics are annotated with formal underpinnings in order to augment them with the semantics of what they depict. Among their many potential uses they provide means for more efficient accessibility of graphical data going beyond the traditional use of textual alternative descriptions, such as natural language interfaces. However, no efficient way of authoring these graphics currently exists. This paper aims to bridge the gap between authoring graphics and enhancing them with semantic formal structures in the form of ontologies by introducing Semantic Annotator for Inkscape (SAI), an authoring tool that allows for seamless addition of semantics to an SVG file supported by a given upper ontology in RDF format. The traditional disjointed approach of authoring a vector image and editing its supporting ontology using independent software tools has thus been unified into a single workspace, improving the efficiency of authoring semantically-enhanced graphics. Evaluation of SAI has shown greatly improved annotation times of semantically-enhanced graphics that can be later used for efficient non-visual natural-language-based content retrieval.

Proceedings Article
01 Jan 2018
TL;DR: The goal is to support the easy querying of interaction concepts both by machine agents but also by developers of applications running in smart environments by presenting an ontology for the domain of interaction.
Abstract: In many smart environments including smart homes, human machine interactions are crucial. Being able to describe, store and query interaction data is an important feature. This especially gains importance when artificial embodied agents (i.e. robotic companions) are present. In order to support querying interaction data at a conceptual level, abstracting from specific and heterogeneous data schemas, we present an ontology for the domain of interaction. To model the interaction domain, the ontology imports two pre-existing ontologies: the Semantic Sensor Network Ontology and the Timeline Ontology. The ontology further includes interaction-relevant concepts as they occur in smart homes but also in other embodied interactive smart environments. We also describe a reference application for a data management and query system for interaction data that builds on this ontology. Our goal is to support the easy querying of interaction concepts both by machine agents but also by developers of applications running in smart environments. We therefore further provide exemplary queries to show the retrieval capabilities of a system that uses our ontology as a proof-of- concept

23 Apr 2018
TL;DR: In this article, the authors claim that the conceptual mode built from text is rarely an ontology and that such a conceptualization is corpus-dependent and does not offer the main properties we expect from ontolo gy, e.g. reusability and soundness.
Abstract: In this article we claim that the conceptual mode lling built from text is rarely an ontology. Such a conceptualization is corpus-dependent and does not offer the main properties we expect from ontolo gy, e.g. reusability and soundness. Furthermore, ontology extracted from text in general does not match ontology defined by expert using a formal language. Such a result is not surprising since ontology is an extra-linguistic co nceptualization whereas knowledge extracted from text is the concern of tex tual linguistics. Incompleteness of text and using rhetorical figures , like synecdoche, deeply modify the perception of the conceptualization we may have. It means that ontological knowledge, which is necessary for text understanding, is not in general embedded into documents. The article will e nd on some remarks about formal languages. If they allow to define "a specif ication of a conceptualization" they nevertheless raise their ow n issues mainly due to their epistemological neutrality. Ontology design remains an epistemological issue.

Proceedings Article
21 Jul 2018
TL;DR: A framework for performing ontology instantiation and population with the structures of a complex mining model involving classification and association rules is designed and implemented for turning the mining model into a context model.
Abstract: The analysis of unstructured text when performed by text mining machine learning algorithm results in mining model holding rules for relationships and dependencies among terms extracted by text preprocessing techniques. The obtained mining model represents knowledge derived from the analyzed text which is hard to interpret as it lacks context. Enhancement of its semantic value can be obtained by implementing logic based approach providing formally defined meaning and interpretation mechanism. The generally accepted form for representation of knowledge for existing domain is by domain-specific ontology. The aim of the paper consists in designing a framework for performing ontology instantiation and population with the structures of a complex mining model involving classification and association rules. Procedures have been designed for annotating them with domain concepts and semantic types. The framework provides for turning the mining model into a context model. Ontology reasoning is implemented to validate the input mining model by rule semantic disambiguation and dependency conceptualization. The framework implementation provides for outputting validated domain-related knowledge base in explicit and machine-readable form as a resource that can be adapted for decision support.

Journal ArticleDOI
TL;DR: The proposed meta- model is conformed towards an ontology driven meta-meta model called, Generalized Ontology Modelling (GOM), which can be further restricted towards distinct models of SOA based applications.
Abstract: Effective modelling has helped in explain, formalize and understand Service Oriented Architecture (SOA) that is a complex architecture style inherently. Yet, a serious gap is still exist in modelling inter dependency between structural and behavioural characteristics of SOA. Beside, lack of precise semantics and formalization in modelling of SOA has made serious challenges in checking consistency over SOA models. In order to address these challenges, in this paper, an ontology driven meta-model has been proposed for SOA. The proposed meta- model is conformed towards an ontology driven meta-meta model called, Generalized Ontology Modelling (GOM). It can be further restricted towards distinct models of SOA based applications. The proposed meta-model is implemented using ontology editorial tool Protege and illustrated using suitable case study.

Posted Content
TL;DR: This paper attempts to establish a link between probabilistic reasoning in PCFG and MEBN by proposing a formal description of PCFG driven by MEBN leading to usage of PR-OWL modeled ontologies in PC FG parsers.
Abstract: Probabilistic context free grammars (PCFG) have been the core of the probabilistic reasoning based parsers for several years especially in the context of the NLP. Multi entity bayesian networks (MEBN) a First Order Logic probabilistic reasoning methodology and is widely adopted and used method for uncertainty reasoning. Further upper ontology like Probabilistic Ontology Web Language (PR-OWL) built using MEBN takes care of probabilistic ontologies which model and capture the uncertainties inherent in the domain's semantic information. The paper attempts to establish a link between probabilistic reasoning in PCFG and MEBN by proposing a formal description of PCFG driven by MEBN leading to usage of PR-OWL modeled ontologies in PCFG parsers.