scholarly journals Process ontology development using natural language processing: a multiple case study

2019 ◽  
Vol 25 (6) ◽  
pp. 1208-1227 ◽  
Author(s):  
Ozge Gurbuz ◽  
Fethi Rabhi ◽  
Onur Demirors
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Multiple Case Study ◽  
Process Models ◽  
Ontology Development ◽  
Process Ontology ◽  
Content Type ◽  
Multiple Case

Purpose Integrating ontologies with process modeling has gained increasing attention in recent years since it enhances data representations and makes it easier to query, store and reuse knowledge at the semantic level. The authors focused on a process and ontology integration approach by extracting the activities, roles and other concepts related to the process models from organizational sources using natural language processing techniques. As part of this study, a process ontology population (PrOnPo) methodology and tool is developed, which uses natural language parsers for extracting and interpreting the sentences and populating an event-driven process chain ontology in a fully automated or semi-automated (user assisted) manner. The purpose of this paper is to present applications of PrOnPo tool in different domains. Design/methodology/approach A multiple case study is conducted by selecting five different domains with different types of guidelines. Process ontologies are developed using the PrOnPo tool in a semi-automated and fully automated fashion and manually. The resulting ontologies are compared and evaluated in terms of time-effort and recall-precision metrics. Findings From five different domains, the results give an average of 70 percent recall and 80 percent precision for fully automated usage of the PrOnPo tool, showing that it is applicable and generalizable. In terms of efficiency, the effort spent for process ontology development is decreased from 250 person-minutes to 57 person-minutes (semi-automated). Originality/value The PrOnPo tool is the first one to automatically generate integrated process ontologies and process models from guidelines written in natural language.

scholarly journals Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder

2020 ◽  
Vol 20 (S11) ◽  
Author(s):  
Jacqueline Peng ◽  
Mengge Zhao ◽  
James Havrilla ◽  
Cong Liu ◽  
Chunhua Weng ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Clinical Manifestations ◽  
Predictive Performance ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Research Articles

Abstract Background Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations. Methods We comparatively evaluated these NLP tools using autism spectrum disorder (ASD) as a case study. We collected 827 ASD-related terms based on previous literature as the benchmark list for performance evaluation. Then, we applied CLAMP, cTAKES, and MetaMap on 544 full-text articles and 20,408 abstracts from PubMed to extract ASD-related terms. We evaluated the predictive performance using precision, recall, and F1 score. Results We found that CLAMP has the best performance in terms of F1 score followed by cTAKES and then MetaMap. Our results show that CLAMP has much higher precision than cTAKES and MetaMap, while cTAKES and MetaMap have higher recall than CLAMP. Conclusion The analysis protocols used in this study can be applied to other neuropsychiatric or neurodevelopmental disorders that lack well-defined terminology sets to describe their phenotypic presentations.

Asymmetric effect of feature level sentiment on product rating: an application of bigram natural language processing (NLP) analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yun Kyung Oh ◽  
Jisu Yi
Keyword(s):  
Natural Language Processing ◽  
Customer Satisfaction ◽  
Natural Language ◽  
Language Processing ◽  
Big Data Analytics ◽  
Service Improvement ◽  
Asymmetric Effect ◽  
Content Type ◽  
Quality Dimensions ◽  
Product Ratings

PurposeThe evaluation of perceived attribute performance reflected in online consumer reviews (OCRs) is critical in gaining timely marketing insights. This study proposed a text mining approach to measure consumer sentiments at the feature level and their asymmetric impacts on overall product ratings.Design/methodology/approachThis study employed 49,130 OCRs generated for 14 wireless earbud products on Amazon.com. Word combinations of the major quality dimensions and related sentiment words were identified using bigram natural language processing (NLP) analysis. This study combined sentiment dictionaries and feature-related bigrams and measured feature level sentiment scores in a review. Furthermore, the authors examined the effect of feature level sentiment on product ratings.FindingsThe results indicate that customer sentiment for product features measured from text reviews significantly and asymmetrically affects the overall rating. Building upon the three-factor theory of customer satisfaction, the key quality dimensions of wireless earbuds are categorized into basic, excitement and performance factors.Originality/valueThis study provides a novel approach to assess customer feature level evaluation of a product and its impact on customer satisfaction based on big data analytics. By applying the suggested methodology, marketing managers can gain in-depth insights into consumer needs and reflect this knowledge in their future product or service improvement.

scholarly journals Self-protective strategies of parents with ADHD and their children as mediated by sensitivity – a multiple-case study

2019 ◽  
Vol 14 (4) ◽  
pp. 278-291
Author(s):  
Milla Syrjänen ◽  
Airi Hautamäki ◽  
Natalia Pleshkova ◽  
Sinikka Maliniemi
Keyword(s):  
Quantitative Methods ◽  
Multiple Case Study ◽  
Adult Attachment Interview ◽  
The Self ◽  
Content Type ◽  
Parental Sensitivity ◽  
Multiple Case ◽  
Protective Strategies ◽  
Attachment Strategies

Purpose The purpose of this paper is to explore the parental sensitivity and self-protective strategies of parents with attention deficit hyperactivity disorder (ADHD) and those of their children. Design/methodology/approach Six parents with ADHD and their under 3-years-old children participated. One parent took part with her both children. The data included seven parent-child dyads. The parents were interviewed with the modified Adult Attachment Interview. Parental sensitivity was assessed using the CARE-Index. The self-protective strategies of the children were assessed with The Strange Situation Procedure or the Preschool Assessment of Attachment. Findings The study showed a variety of the self-protective strategies of parents with ADHD as well as those of their children. Three subgroups were formed on the basis of risk as indicated by Crittenden’s gradient of transformation of information. Parents displayed complex self-protective strategies as well as unresolved traumas, which impaired their sensitivity and ability to engage in mutual regulation of arousal and emotion. The parents’ needs of self-protection compromised their ability to protect and comfort their child that is their sensitivity. The children’s protective strategies matched those of their parents in regard to complexity as mediated by parental sensitivity. Originality/value This multiple-case study demonstrates new ideas to be tested with quantitative methods in larger samples. There are no previous studies which have examined both the attachment strategies and sensitivity of parents with ADHD connecting these with the evolving attachment strategies of their children.

scholarly journals Natural Language Processing (NLP) and Its Impact across Industries – Unlocking the True Potential of Digital Healthcare (A Case Study Approach)

2021 ◽  
pp. 86-98
Author(s):  
Sourajit Roy ◽  
Pankaj Pathak ◽  
S. Nithya
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Computational Models ◽  
M2m Communication ◽  
Digital Revolution ◽  
Language Complexity ◽  
Study Approach ◽  
Data Variability

During the advent of the 21st century, technical breakthroughs and developments took place. Natural Language Processing or NLP is one of their promising disciplines that has been increasingly dynamic via groundbreaking findings on most computer networks. Because of the digital revolution the amounts of data generated by M2M communication across devices and platforms such as Amazon Alexa, Apple Siri, Microsoft Cortana, etc. were significantly increased. This causes a great deal of unstructured data to be processed that does not fit in with standard computational models. In addition, the increasing problems of language complexity, data variability and voice ambiguity make implementing models increasingly harder. The current study provides an overview of the potential and breadth of the NLP market and its acceptance in industry-wide, in particular after Covid-19. It also gives a macroscopic picture of progress in natural language processing research, development and implementation.

Higher authority organizational stressors among higher education deans: a multiple case study

2018 ◽  
Vol 10 (3) ◽  
pp. 333-343 ◽  
Author(s):  
Alfred Huan Zhi Chan ◽  
Mohd Dahlan Malek ◽  
Ferlis Bahari
Keyword(s):  
Higher Education ◽  
Multiple Case Study ◽  
Education Institution ◽  
Higher Education Management ◽  
Case Study Methodology ◽  
Content Type ◽  
Organizational Stressors ◽  
Multiple Case ◽  
Education Deans

Purpose The purpose of this paper is to identify higher authority organizational stressors encountered by higher education deans. Design/methodology/approach This current research employed a qualitative approach utilizing a contextual paradigm with a multiple case study methodology. Findings Out of ten investigated deans in a public higher education institution in Malaysia, nine reported experiences of organizational stressor elements arising from higher authority. Three non-overlapping subthemes were systematically discovered. Practical implications Successful identification of these higher authority organizational stressors has implications for higher education management policies. Policies that reduce or eliminate these stressors may create a positive and progressive environment for deans and the higher education field. Originality/value This study will thus serve to promote a deeper understanding of higher authority organizational stressors encountered by higher education deans.

Adoption strategies of social media in B2B firms: a multiple case study approach

2018 ◽  
Vol 33 (5) ◽  
pp. 730-743 ◽  
Author(s):  
Maryam Lashgari ◽  
Catherine Sutton-Brady ◽  
Klaus Solberg Søilen ◽  
Pernilla Ulfvengren
Keyword(s):  
Social Media ◽  
Multinational Corporations ◽  
Multiple Case Study ◽  
Communication Strategy ◽  
Case Study Approach ◽  
Content Type ◽  
Study Approach ◽  
Study Results ◽  
Multiple Case

PurposeThe purpose of this study is to clarify business-to-business (B2B) firms’ strategies of social media marketing communication. The study aims to explore the factors contributing to the formation and adoption of integration strategies and identify who the B2B firms target.Design/methodology/approachA multiple case study approach is used to compare four multinational corporations and their practices. Face-to-face interviews with key managers, and extensive readings and observations of the firms’ websites and social media platforms have been conducted.FindingsThe study results in a model, illustrating different processes of selection, adoption and integration involved in the development of social media communication strategy for B2B firms. Major factors involved in determining the platform type, and strategies used within different phases and processes are identified.Research limitations/implicationsAs the chosen methodology may limit generalizability, further research is encouraged to test the model within a B2B context especially within small and medium enterprises as only large multinational corporations were investigated in this study.Practical implicationsThe paper provides insight into how B2B marketers can align social media with their firms’ goals through the strategic selection of platforms to reach the targeted audience and communicate their message.Originality/valueThe study uncovers the benefits gained by B2B firms’ through interaction with individuals on social media. This is a significant contribution as the value of such interaction was previously undefined and acted as a barrier for adopting social media in some B2B firms.

Warehouse configuration in omni-channel retailing: a multiple case study

2019 ◽  
Vol 50 (5) ◽  
pp. 509-533
Author(s):  
Joakim Hans Kembro ◽  
Andreas Norrman
Keyword(s):  
Case Studies ◽  
Conceptual Models ◽  
Construction Material ◽  
Multiple Case Study ◽  
Consumer Electronics ◽  
Future Research ◽  
Content Type ◽  
Automation Systems ◽  
Multiple Case

Purpose The purpose of this study is to explore warehouse configuration in omni-channel retailing. Design/methodology/approach A multiple case study is conducted with six large omni-channel retailers from three different sectors. Findings The study shows an increase in the number, variation and frequency of flows passing through omni-channel warehouses. Along with an increased variety of stock keeping units (including singles vs multipacks), there is an increase in the complexity of planning and coordination of order fulfillment. Retailers test a mix of different solutions for storage and picking and partly shift focus to advanced sorting operations. The companies already have or plan to invest in substantial automation systems, which emphasize the importance of capturing and using accurate master data. Research limitations/implications The study highlights the need to understand the interrelations and co-development of configuration elements in omni-channel warehousing. The findings also suggest that a successful transformation requires increased collaboration with upstream and downstream partners. Conceptual models are developed to illustrate strategies and development paths in omni-channel warehousing, and suggestions for future research are summarized in a research agenda. A research limitation is the focus on Swedish retailers in three sectors (fashion, consumer electronics and DIY/construction material). Future studies can include additional sectors, extend the geographical scope and explore cross-regional differences. Practical implications As one of the few deeper case studies on omni-channel warehousing, practitioners will find new configurations described and analyzed here. Along with conceptual models, a synthesis of challenges and potential solutions are presented to support retailers’ practical analysis and decision making. Originality/value This is one of the first multiple case studies that go deeper into omni-channel warehouse configuration, which is of increasing importance to both scholars and practitioners in the field.

Successful approaches for implementing additive manufacturing

2020 ◽  
Vol 16 (2) ◽  
pp. 131-148
Author(s):  
Robert Martens ◽  
Susan K. Fan ◽  
Rocky J. Dwyer
Keyword(s):  
Additive Manufacturing ◽  
The Netherlands ◽  
Business Models ◽  
Multiple Case Study ◽  
High Tech ◽  
Manufacturing Companies ◽  
Content Type ◽  
Multiple Case ◽  
Qualitative Multiple Case Study

PurposeThe purpose of this qualitative, multiple-case study was to explore the successful strategies that managers of light and high-tech small and medium-sized manufacturing companies in the Netherlands, use to adopt additive manufacturing (AM) technology into their business models.Design/methodology/approachA qualitative, multiple-case study approach was used. The participants for this study consisted of executive-level managers of light and high-tech manufacturing companies in the Netherlands. Company documents were studied, and individual interviews were undertaken with participants to gain an understanding of the strategies they used to adopt AM technology into their business models.FindingsThree significant themes emerged from the data analysis: identify business opportunities for AM technology, experiment with AM technology and embed AM technology.Research limitations/implicationsThe findings of this study could be of advantage to industry leaders and manufacturing managers who are contemplating to adopt AM in their business models.Originality/valueThis study may contribute to the further proliferation of AM technology. Industry leaders may also gain a clearer understanding of the effects of 3DP on local employment. The results of the study may also work as a catalyst for increased awareness for manufacturing firm leaders who have not yet considered the opportunities and threats AM technology presents to their organizations.

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