An Enhanced Personal Profile Ontology for Software Requirements Engineering Tasks Allocation

Usip, Patience U.; Udo, Edward N.; Umoeka, Ini

doi:10.1007/978-3-030-91305-2_15

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…Domain ontologies have been used previously for several tasks. To capture both static and dynamic features of personal data, Usip et al (2021) created an upgraded personal profile ontology for software requirements engineering work allocation. They combined elements of many pre-existing ontologies, such as Neon and Methontology, to create this ontology.…”

Section: Research Problemmentioning

confidence: 99%

A robust approach for aspect-based sentiment analysis using deep learning and domain ontologies

Sharma,

Saraswat

2024

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Purpose The purpose of this research study is to improve sentiment analysis (SA) at the aspect level, which is accomplished through two independent goals of aspect term and opinion extraction and subsequent sentiment classification. Design/methodology/approach The proposed architecture uses neighborhood and dependency tree-based relations for target opinion extraction, a domain–ontology-based knowledge management system for aspect term extraction, and deep learning techniques for classification. Findings The authors use different deep learning architectures to test the proposed approach of both review and aspect levels. It is reported that Vanilla recurrent neural network has an accuracy of 83.22%, long short-term memory (LSTM) is 89.87% accurate, Bi-LSTM is 91.57% accurate, gated recurrent unit is 65.57% accurate and convolutional neural network is 82.33% accurate. For the aspect level analysis, ρaspect comes out to be 0.712 and Δ2aspect is 0.384, indicating a marked improvement over previously reported results. Originality/value This study suggests a novel method for aspect-based SA that makes use of deep learning and domain ontologies. The use of domain ontologies allows for enhanced aspect identification, and the use of deep learning algorithms enhances the accuracy of the SA task.

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Section: Research Problemmentioning

confidence: 99%

A robust approach for aspect-based sentiment analysis using deep learning and domain ontologies

Sharma,

Saraswat

2024

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“…Most personal profile ontologies model static information, thereby leaving out dynamic data on users’ activities and behaviors. An ontology including static and dynamic properties of the personal profile is proposed in (Usip et al , 2021). The authors present the enhanced personal profile ontology, which is designed to support software requirements engineering task allocation; a domain different from that of hospitality.…”

Section: Hotel Room Personalizationmentioning

confidence: 99%

Hotel room personalization via ontology and rule-based reasoning

Ojino

Mich

Mvungi

2022

IJWIS

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Purpose The increasingly competitive hotel industry and emerging customer trends where guests are more discerning and want a personalized experience has led to the need of innovative applications. Personalization is much more important for hotels, especially now in the post-COVID lockdown era, as it challenges their business model. However, personalization is difficult to design and realize due to the variety of factors and requirements to be considered. Differences are both in the offer (hotels and their rooms) and demand (customers’ profiles and needs) in the accommodation domain. As for the implementation, critical issues are in hardware-dependent and vendor-specific Internet of Things devices which are difficult to program. Additionally, there is complexity in realizing applications that consider varying customer needs and context via existing personalization options. This paper aims to propose an ontological framework to enhance the capabilities of hotels in offering their accommodation and personalization options based on a guest’s characteristics, activities and needs. Design/methodology/approach A research approach combining both quantitative and qualitative methods was used to develop a hotel room personalization framework. The core of the framework is a hotel room ontology (HoROnt) that supports well-defined machine-readable descriptions of hotel rooms and guest profiles. Hotel guest profiles are modeled via logical rules into an inference engine exploiting reasoning functionalities used to recommend hotel room services and features. Findings Both the ontology and the inference engine module have been validated with promising results which demonstrate high accuracy. The framework leverages user characteristics, and dynamic contextual data to satisfy guests’ needs for personalized service provision. The semantic rules provide recommendations to both new and returning guests, thereby also addressing the cold start issue. Originality/value This paper extends HoROnt in two ways, to be able to add: instances of the concepts (room characteristics and services; guest profiles), i.e. to create a knowledge base, and logical rules into an inference engine, to model guests’ profiles and to be used to offer personalized hotel rooms. Thanks to the standards adopted to implement personalization, this framework can be integrated into existing reservation systems. It can also be adapted for any type of accommodation since it is broad-based and personalizes varying features and amenities in the rooms.

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“…This paper is an extension of our earlier work originally presented in the Knowledge Graph and Semantic Web Conference 2021 with the proceedings published as a book in Communications in Computer and Information Science, Springer (Usip et al, 2021). The conference paper presented the design and development of the ontology without applying it to any specific domain while this extended work applies the developed ontology for personnel appraisal.…”

Section: Introductionmentioning

confidence: 98%

“…The application of the developed e-PPO produces a smart r esum e from the populated ontology (Usip et al, 2021). A r esum e consists of personal information, education information, work experience, skills, qualifications, preferences parts etc.…”

Section: Introductionmentioning

confidence: 99%

Applied personal profile ontology for personnel appraisals

Usip

Udo

Umoeka

2022

IJWIS

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Purpose The purpose of this paper is to apply the earlier enhanced personal profile ontology (e-PPO) developed by the authors as a case study for the appraisal of the lecturers in the department of computer science, University of Uyo, Uyo for the purposes of promotions. The developed e-PPO was a sample smart résumé for the selection of the best among three personnel using linguistic variables and formal rules representing the combination of the criteria and subcriteria was illustrated which was used to allocate competent personnel for software requirement engineering tasks. The need for the use of the smart resume for appraisal purposes was pointed out in the conference paper, calling for the applicant’s data to be inputted into the enhanced personal profile ontology (e-PPO) for personnel appraisa. Design/methodology/approach Appraisal is a regular review of employees’ performances and their overall contribution to the organization they are working for. The availability of a web application for personnel appraisal requires PPO which includes both static and dynamic features. Personal profile is often modified for several purposes calling for augmentation and annotation when needs arise. Resume is one resulting extract from personal profile and often contain slightly different information based on needs. The urgent preparation of resume may introduce bias and incorrect information for the sole aim of projecting the personnel as being qualified for the available job. Religious and gender biases may sometimes be observed during appointments of new personnel, which may not be the case during appraisals for promotions or reassignment of tasks because such biases become insignificant given the fact that job targets and the skills needed are already set and the appraisals passes through several phases that are not determined by a single individual. This work therefore applied the earlier developed e-PPO for appraisal of the academic staff of the department of computer science, university of Uyo, Uyo, Nigeria. A mixed approach of existing ontologies like Methontology and Neon have been followed in the creation of the e-PPO, which is a constraint-based semantic data model tested using Protégé inbuilt reasoner with its updated plugins. Upon application of e-PPO on personnel appraisals, promotion and selection of employee for specific assignments in any organization is possible using the smart resume. Findings The use of the smart resume reduces the numerous task that would have been taken up by the human resource team, thereby reducing the processing time for the appraisals. The appraisal task is done void of biases of any kind such as gender and religion. Originality/value This work is an extension of the original work done by the authors.

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An Enhanced Personal Profile Ontology for Software Requirements Engineering Tasks Allocation

Cited by 4 publications

References 18 publications

A robust approach for aspect-based sentiment analysis using deep learning and domain ontologies

A robust approach for aspect-based sentiment analysis using deep learning and domain ontologies

Hotel room personalization via ontology and rule-based reasoning

Applied personal profile ontology for personnel appraisals

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