Document Space Adapted Ontology: Application in Query Enrichment

2006 ◽  
pp. 46-57 ◽  
Author(s):  
Stein L. Tomassen ◽  
Jon Atle Gulla ◽  
Darijus Strasunskas
Keyword(s):  
Ontology Application

Easy ontology, application conditions and infinite regress

Analysis ◽  
2018 ◽  
Vol 78 (4) ◽  
pp. 605-614 ◽  
Author(s):  
Andrew Brenner
Keyword(s):  
Infinite Regress ◽  
Ontology Application

A Note on Optimal Function for Similarity Measure in Ontology Application

2013 ◽  
Vol 748 ◽  
pp. 967-971
Author(s):  
Wei Gao ◽  
Tian Wei Xu ◽  
Li Liang ◽  
Jian Hou Gan
Keyword(s):  
Information Retrieval ◽  
Likelihood Ratio ◽  
Similarity Measure ◽  
Equivalence Classes ◽  
Ontology Mapping ◽  
Important Research ◽  
Research Topics ◽  
Similarity Calculation ◽  
Optimal Function ◽  
Ontology Application

Ontology similarity calculation and ontology mapping are important research topics in information retrieval. One method for ontology similarity measure is using multi-dividing approach. Assume that the notation and terminology used but undefined in this paper can be found in [4] and [5]. We show that the assumption of strict ordering of xi*can be relaxed to allow some ties in the likelihood ratio. The same proof remains true if we consider equivalence classes defined by the likelihood ratio and relabel xi* as its equivalence class denoted by [xi*].

scholarly journals Ontology application and use at the ENCODE DCC

Database ◽  
2015 ◽  
Vol 2015 ◽  
Author(s):  
Venkat S. Malladi ◽  
Drew T. Erickson ◽  
Nikhil R. Podduturi ◽  
Laurence D. Rowe ◽  
Esther T. Chan ◽  
...  
Keyword(s):  
Ontology Application

OAM: An Ontology Application Management Framework for Simplifying Ontology-Based Semantic Web Application Development

2016 ◽  
Vol 26 (01) ◽  
pp. 115-145 ◽  
Author(s):  
Marut Buranarach ◽  
Thepchai Supnithi ◽  
Ye Myat Thein ◽  
Taneth Ruangrajitpakorn ◽  
Thanyalak Rattanasawad ◽  
...  
Keyword(s):  
Semantic Web ◽  
Web Application ◽  
Web Applications ◽  
Data Publishing ◽  
Application Framework ◽  
Application Development ◽  
Development Environment ◽  
Application Management ◽  
Efficient Performance ◽  
Ontology Application

Although the Semantic Web data standards are established, ontology-based applications built on the standards are relatively limited. This is partly due to high learning curve and efforts demanded in building ontology-based Semantic Web applications. In this paper, we describe an ontology application management (OAM) framework that aims to simplify creation and adoption of ontology-based application that is based on the Semantic Web technology. OAM introduces an intermediate layer between user application and programming and development environment in order to support ontology-based data publishing and access, abstraction and interoperability. The framework focuses on providing reusable and configurable data and application templates, which allow the users to create the applications without programming skill required. Three forms of templates are introduced: database to ontology mapping configuration, recommendation rule and application templates. We describe two case studies that adopted the framework: activity recognition in smart home domain and thalassemia clinical support system, and how the framework was used in simplifying development in both projects. In addition, we provide some performance evaluation results to show that, by limiting expressiveness of the rule language, a specialized form of recommendation processor can be developed for more efficient performance. Some advantages and limitations of the application framework in ontology-based applications are also discussed.

scholarly journals OntoCAT – an integrated programming toolkit for common ontology application tasks

2011 ◽  
Author(s):  
Tomasz Adamusiak ◽  
Tomasz Adamusiak ◽  
Natalja Kurbatova ◽  
Morris Swertz ◽  
Helen Parkinson
Keyword(s):  
Ontology Application

scholarly journals Semantic Approach for Al-Quran Knowledge Representation in Islamic Knowledge Management Framework

2021 ◽  
Vol 02 (01) ◽  
Author(s):  
Azman Ta’a ◽  
◽  
Muhammad Shakirin Shaari @ Hj Ashari ◽  
Ahmad Suki Che Mohamed Arif ◽  
Muhamad Shahbani Abu Bakar ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Data Model ◽  
Knowledge Processing ◽  
Semantic Approach ◽  
Structural Explanation ◽  
Management Framework ◽  
Evaluation Test ◽  
Ontology Application ◽  
Searching Method

Using ontology data model to accurately represent Al-Quran knowledge using its inherent structure of Division (Juz), Chapter (Surah), and Verse (Ayah) should be done within the framework of the Islamic Knowledge Management (IKM). Data modelling neglecting the IKM framework would result in inaccuracy and irrelevant result in knowledge processing activities involving the Al-Quran. Many of the current approaches utilizing conventional knowledge management methods such as taxonomy, hierarchy, or tree structure are limited in the sense that they only define the concepts of knowledge without relating it to a theme that defined from corpus of Islamic knowledge. In the case of Al-Quran, a classification of themes from background knowledge are important to provide a structural explanation of the knowledge and to ensure that the results obtained from a searching function of the corpus of the knowledge will result in an accurate and appropriate meaning intended by the Islamic knowledge. The aims of this paper is to demonstrate the construction of Al-Quran ontology and elaborate the searching method for representing and retrieving the relevance and accurate verses toward the theme of Al-Quran by using the semantic-based approach. The specification of Al-Quran ontology of which the prototype application was built on has been validated by experts. The evaluation test of the Al-Quran ontology application furthermore shows high precision result from searching functions done. With a good level of accuracy achieved from the test, it is hopeful that Al-Quran ontology application will provide a new experience of Al-Quran themes searching and browsing within the IKM framework for the Al-Quran readers. A capability to efficiently and accurately performing search of Al-Quran will certainly improve their understanding of Al-Quran contents.

Application of Ontology from Course and Forum Discussion Learning Content

2015 ◽  
Vol 2 ◽  
pp. 24
Author(s):  
Hazalina Hashim
Keyword(s):  
Online Survey ◽  
Semantic Knowledge ◽  
Learning System ◽  
Three Dimensions ◽  
Positive Perception ◽  
Online Learners ◽  
Effective Learning ◽  
Learning Content ◽  
E Learning ◽  
Ontology Application

The capability of ontology application to add meaning to information, indexed in such a way that it can be reused, searched, processed and shared has been extensively explored and recognized in e-learning education. As such, it is the interest of this paper to apply the use of ontology from course module and forum discussion learning content in e-learning setting.  Thus, the ontology designed with SKOS specification is used to structure into concepts and relationships in order to develop and highlight the essential learning content. Furthermore, a semantic forum system is proposed as a mechanism to represent the ontology designed into semantic knowledge representation for learner to easily access, search and navigate the relevant knowledge of interest. This study evaluates the effectiveness of the proposed system along with three dimensions namely learners’ perceptions, system design perceptions, and system content perceptions. Accordingly, a close-ended online survey was developed and administered to 74 online learners. The findings demonstrate positive perception that contributes to effective learning system that able to enhance the understanding of course taught.

A Knowledge Model of Digital Evidence Review Elements Based on Ontology

2020 ◽  
pp. 281-290
Author(s):  
Ning Wang
Keyword(s):  
Knowledge Base ◽  
Domain Ontology ◽  
Digital Evidence ◽  
Knowledge Model ◽  
Ontology Construction ◽  
Model Based ◽  
Application Ontology ◽  
Evidence Review ◽  
Ontology Application ◽  
Knowledge Classification

As existing methods cannot express, share, and reuse the digital evidence review information in a unified manner, a solution of digital evidence review elements knowledge base model based on ontology is presented. Firstly, combing with the multi-source heterogeneous characteristic of digital evidence review knowledge, classification and extraction are accomplished. Secondly, according to the principles of ontology construction, the digital evidence review elements knowledge base model which includes domain ontology, application ontology, and atomic ontology is established. Finally, model can effectively acquire digital evidence review knowledge by analyzing review scenario.

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