Bridging Upper Ontology and Modular Ontology Modeling: a Tool and Evaluation

2020 ◽

Author(s):

Cogan Shimizu ◽

Pascal Hitzler ◽

Adila Krisnadhi

Keyword(s):

Design Patterns ◽

Ontology Engineering ◽

Web Ontology Language ◽

Ontology Language ◽

Ontology Modeling ◽

Ontology Design ◽

Modular Ontology ◽

The Web

We provide an in-depth example of modular ontology engineering with ontology design patterns. The style and content of this chapter is adapted from previous work and tutorials on Modular Ontology Modeling. It offers expanded steps and updated tool information. The tutorial is largely self-contained, but assumes that the reader is familiar with the Web Ontology Language OWL; however, we do briefly review some foundational concepts. By the end of the tutorial, we expect the reader to have an understanding of the underlying motivation and methodology for producing a modular ontology.

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Intelligent Petrol Station Recommender Based on Context Ontology and Rule Inference

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.303-306.1412 ◽

2013 ◽

Vol 303-306 ◽

pp. 1412-1415

Author(s):

Hui Zuo ◽

Dan Xiang Ai ◽

Jun Yang

Keyword(s):

Recommender System ◽

Domain Ontology ◽

Petrol Station ◽

Ontology Modeling ◽

Ontology Model ◽

Rule Inference ◽

Upper Ontology

An intelligent mobile petrol station recommender system based on context ontology and rule inference is deigned. The approach of context ontology modeling specific for mobile recommendation is discussed. And a two-level context ontology model including upper ontology and domain ontology used in petrol station recommender is developed. The generation of recommendation rules based on the context ontologies and the process of the rule inference for recommendation are also demonstrated.

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Context Ontology Modeling for Mobile Petrol Station Recommendation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.291-294.2849 ◽

2013 ◽

Vol 291-294 ◽

pp. 2849-2852

Author(s):

Hui Zuo ◽

Dan Xiang Ai

Keyword(s):

Domain Ontology ◽

Use Case ◽

Context Modeling ◽

Petrol Station ◽

Modeling Approach ◽

Ontology Modeling ◽

Ontology Model ◽

Upper Ontology

To support the personalized mobile recommendation service, a context modeling approach based on ontology was proposed. The role of context ontologies in mobile recommenders was discussed, and under the application background of petrol station recommendation, a two-level context ontology model was designed. The model contains an upper ontology to describe general concepts, and a domain ontology extended from the upper ontology. The context ontology provides formalizations representing the mainly entities including users, objects and contexts, and their interactive relationships in mobile recommendation environments. Finally, a use case of the instantiated context ontology was demonstrated.

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Construction of Folksonomy-Based Microcontents Using Upper Ontology Modeling

Journal of the Korean Society for information Management ◽

10.3743/kosim.2011.28.4.161 ◽

2011 ◽

Vol 28 (4) ◽

pp. 161-182

Author(s):

Seung-Min Lee

Keyword(s):

Ontology Modeling ◽

Upper Ontology

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An Uncertain Context Ontology Modeling and Reasoning Approach Based on D-S Theory

JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY ◽

10.3724/sp.j.1146.2009.01015 ◽

2010 ◽

Vol 32 (8) ◽

pp. 1806-1811 ◽

Cited By ~ 4

Author(s):

Yan-na Li ◽

Xiu-quan Qiao ◽

Xiao-feng Li

Keyword(s):

Ontology Modeling

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Personalized cloud service review analysis based on modularized ontology

Online Information Review ◽

10.1108/oir-06-2019-0207 ◽

2020 ◽

Vol 44 (5) ◽

pp. 953-975

Author(s):

Emna Ben-Abdallah ◽

Khouloud Boukadi ◽

Mohamed Hammami ◽

Mohamed Hedi Karray

Keyword(s):

Knowledge Base ◽

Positive Impact ◽

Cloud Service ◽

Service Evaluation ◽

End Users ◽

Cloud Services ◽

Limited Information ◽

Content Type ◽

Ontology Language ◽

Modular Ontology

PurposeThe purpose of this paper is to analyze cloud reviews according to the end-user context and requirements.Design/methodology/approachpropose a comprehensive knowledge base composed of interconnected Web Ontology Language, namely, modular ontology for cloud service opinion analysis (SOPA). The SOPA knowledge base will be the basis of context-aware cloud service analysis using consumers' reviews. Moreover, the authors provide a framework to evaluate cloud services based on consumers' reviews opinions.FindingsThe findings show that there is a positive impact of personalizing the cloud service analysis by considering the reviewers' contexts in the performance of the framework. The authors also proved that the SOPA-based framework outperforms the available cloud review sites in term of precision, recall and F-measure.Research limitations/implicationsLimited information has been provided in the semantic web literature about the relationships between the different domains and the details on how that can be used to evaluate cloud service through consumer reviews and latent opinions. Furthermore, existing approaches are lacking lightweight and modular mechanisms which can be utilized to effectively exploit information existing in social media.Practical implicationsThe SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.Originality/valueThe SOPA ontology is capable of representing the content of a product/service as well as its related opinions, which are extracted from the customer's reviews written in a specific context. Furthermore, the SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.

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