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1 – 10 of 32Somayeh Tamjid, Fatemeh Nooshinfard, Molouk Sadat Hosseini Beheshti, Nadjla Hariri and Fahimeh Babalhavaeji
The purpose of this study is to develop a domain independent, cost-effective, time-saving and semi-automated ontology generation framework that could extract taxonomic concepts…
Abstract
Purpose
The purpose of this study is to develop a domain independent, cost-effective, time-saving and semi-automated ontology generation framework that could extract taxonomic concepts from unstructured text corpus. In the human disease domain, ontologies are found to be extremely useful for managing the diversity of technical expressions in favour of information retrieval objectives. The boundaries of these domains are expanding so fast that it is essential to continuously develop new ontologies or upgrade available ones.
Design/methodology/approach
This paper proposes a semi-automated approach that extracts entities/relations via text mining of scientific publications. Text mining-based ontology (TmbOnt)-named code is generated to assist a user in capturing, processing and establishing ontology elements. This code takes a pile of unstructured text files as input and projects them into high-valued entities or relations as output. As a semi-automated approach, a user supervises the process, filters meaningful predecessor/successor phrases and finalizes the demanded ontology-taxonomy. To verify the practical capabilities of the scheme, a case study was performed to drive glaucoma ontology-taxonomy. For this purpose, text files containing 10,000 records were collected from PubMed.
Findings
The proposed approach processed over 3.8 million tokenized terms of those records and yielded the resultant glaucoma ontology-taxonomy. Compared with two famous disease ontologies, TmbOnt-driven taxonomy demonstrated a 60%–100% coverage ratio against famous medical thesauruses and ontology taxonomies, such as Human Disease Ontology, Medical Subject Headings and National Cancer Institute Thesaurus, with an average of 70% additional terms recommended for ontology development.
Originality/value
According to the literature, the proposed scheme demonstrated novel capability in expanding the ontology-taxonomy structure with a semi-automated text mining approach, aiming for future fully-automated approaches.
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Keywords
Miquel Centelles and Núria Ferran-Ferrer
Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific…
Abstract
Purpose
Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.
Design/methodology/approach
This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.
Findings
This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.
Originality/value
The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.
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Security assurance evaluation (SAE) is a well-established approach for assessing the effectiveness of security measures in systems. However, one aspect that is often overlooked in…
Abstract
Purpose
Security assurance evaluation (SAE) is a well-established approach for assessing the effectiveness of security measures in systems. However, one aspect that is often overlooked in these evaluations is the assurance context in which they are conducted. This paper aims to explore the role of assurance context in system SAEs and proposes a conceptual model to integrate the assurance context into the evaluation process.
Design/methodology/approach
The conceptual model highlights the interrelationships between the various elements of the assurance context, including system boundaries, stakeholders, security concerns, regulatory compliance and assurance assumptions and regulatory compliance.
Findings
By introducing the proposed conceptual model, this research provides a framework for incorporating the assurance context into SAEs and offers insights into how it can influence the evaluation outcomes.
Originality/value
By delving into the concept of assurance context, this research seeks to shed light on how it influences the scope, methodologies and outcomes of assurance evaluations, ultimately enabling organizations to strengthen their system security postures and mitigate risks effectively.
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Chi-Un Lei, Wincy Chan and Yuyue Wang
Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how…
Abstract
Purpose
Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.
Design/methodology/approach
In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.
Findings
The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.
Research limitations/implications
The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.
Originality/value
The proposed approach explores the possibility of using machine learning for SDG classifications in scale.
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Pierre Jouan and Pierre Hallot
The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information…
Abstract
Purpose
The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.
Design/methodology/approach
This research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.
Findings
This paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.
Originality/value
The framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.
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Ewald Aschauer and Reiner Quick
This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.
Abstract
Purpose
This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.
Design/methodology/approach
In this qualitative study guided by the theoretical framework of institutional theory, the authors conducted 25 semi-structured interviews in seven European countries, including 16 interviews with audit partners from Big 4 firms, 6 with audit team members, 2 with interviewees from second-tier audit firms and 1 with a member of an oversight body.
Findings
The authors show that the central rationale for audit firms to implement SSCs is economic rather than external legitimacy. The authors find that SSC implementation has substantial effects on audit practices, particularly those related to standardisation, coordination and monitoring activities. The authors also highlight the potential impacts on audit quality.
Originality/value
By exploring the motivation for and effects of SSC implementation amongst audit firms, the authors offer insights into the best practices related to subsequent change processes and audit quality.
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This paper aims to introduce a growth comprehensive pattern to explain the phenomenon of individual foreign investment, first at the global level and then at the regional level…
Abstract
Purpose
This paper aims to introduce a growth comprehensive pattern to explain the phenomenon of individual foreign investment, first at the global level and then at the regional level. The patterns are developed based on a number of main theories with grounded theory (GT) as the foundation, distributed on the two pull and push forces of international business theory and migration theory; simultaneously, it is classified on the three levels (attribute–consequence–value [ACV]) of means-end theory.
Design/methodology/approach
An embedded method is applied to generate two complementary datasets from two approaches: in-depth interviews and secondary data analysis.
Findings
In this structure, the investor plays a central role as the decision-maker based on the entrepreneur's motives for internationalization (economics-driven and psychology-driven factors) and the householders' motives for emigration (aspiration and access capabilities). The external forces considered are a push from the home country (structures) and pull from the host country (immigrant investment programs [IIPs]), in which the factor of (dis)trust/misconception as a moderator has an additional impact on this mobility. Demographic factors such as gender, region, generation/age, level of education, religion and occupation generally describe the characteristics of each specific target group.
Research limitations/implications
This paper is to develop a conceptual framework.
Originality/value
The results of this study, in addition to fulfilling its own objectives, will also serve as the foundation for further research in several scientific fields such as economics, sociology and politics.
Peer review
The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-12-2022-0786
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