Ontology Merging in the Context of a Semantic Web Expert System

Verhodubs, Olegs; Grundspeņķis, Jānis

doi:10.1007/978-3-642-41360-5_15

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…Thus, to summarize the above information about using ontologies in the field of requirements engineering: Requirements management suffers from many limitations, such as: Incompleteness, consistency, and conflict identification and tracking, especially with a huge number of requirements; therefore, the use of semantic technologies looks hopeful for addressing these limitations [29].…”

Section: Literature Reviewmentioning

confidence: 99%

An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

Taye¹,

Ghoul²

2023

JSEA

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The paper presents a new approach to managing software requirement elicitation techniques with a high level of analyses based on domain ontology techniques, where we established a mapping between user scenario, structured requirement, and domain ontology techniques to improve many attributes such as requirement consistency, completeness and eliminating duplicate requirements to reduce risk of overrun time and budgets. One of the main targets of requirement engineering is to develop a requirement document with high quality. So, we proposed a user interface to collect all vital information about the project directly from the regular user and requirement engineering; After that, the proposal will generate an ontology based on semantic relations and rules. Requirements Engineering tries to keep requirements throughout a project's life cycle consistent necessities clear, and up to date. This prototype allows mapping requirement scenarios into ontology elements for semantically interrupted. The general points of our prototype are to guarantee the identification requirements and improved nature of the Software Requirements Specification (SRS) by solving incomplete and conflicting information in the requirements specification.

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Section: Literature Reviewmentioning

confidence: 99%

An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

Taye¹,

Ghoul²

2023

JSEA

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“…Ontology merging is the process of a new ontology creation, which is the union of the source ontologies. The original ontologies have similar or overlapping domains but they are unique and not revisions of the same ontology [35].…”

Section: Fig 2 Detailed Architecture Of the Proposed Solutionmentioning

confidence: 99%

A Social Profile Ontology to Enhance Learner Experience in MOOCs

Zankadi

Hilal²,

Idrissi

et al. 2022

Int. J. Emerg. Technol. Learn.

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Learners are more active and interactive interactive in social media as they freely express themselves and share their thoughts and feeling which generates much useful information about their characteristics. However, the same learners are not usually interactive in MOOCs as much as they do in social media. Therefore, focusing on the Learner’s social profile is a key component towards a successful and enriched experience of learning. Especially that MOOCs offer the possibility to sign up using social media accounts. Thereby, profile modelling is an essential step to capture the knowledge about the learners. In this paper, we aim to explore the information generated by the learner’s participation in social media and combine it with his characteristics in MOOCs. Our approach is based on implementing an ontological learner profile that combines other ontologies (IMS-LIP standard, FOAF, and SIOC ontology) as well as some of the major concepts that describe a user in social media. The result of our solution is a social profile ontology (SPOnt) that describes the main concepts of a learner in each environment (MOOCs and social media). We rely on ontology mapping and merging techniques to maintain the semantic links between the different concepts of the two implemented ontologies.

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“…As discussed in [19], merging multiple sources of information can be applied in many different scenarios like distributed databases, multi-agent systems, data warehousing, etc., where it is necessary to integrate multiple databases into a single and preferably consistent database. One of the most relevant applications of merging is in the integration of expert systems [50], where each one has a belief base representing its belief state, which can be either knowledge expressed in a propositional language; or (a subset of) a first-order logic.…”

Section: Belief Change and Knowledge Mergingmentioning

confidence: 99%

Merging existential rules programs in multi-agent contexts through credibility accrual

Deagustini

Teze

Martínez

et al. 2021

Information Sciences

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Ontology Merging in the Context of a Semantic Web Expert System

Cited by 5 publications

References 3 publications

An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

A Social Profile Ontology to Enhance Learner Experience in MOOCs

Merging existential rules programs in multi-agent contexts through credibility accrual

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