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1 – 10 of 41
Article
Publication date: 8 March 2024

Feng Zhang, Youliang Wei and Tao Feng

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to…

Abstract

Purpose

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.

Design/methodology/approach

This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.

Findings

Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.

Originality/value

This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

Details

International Journal of Web Information Systems, vol. 20 no. 3
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 22 February 2024

Ranjeet Kumar Singh

Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The…

181

Abstract

Purpose

Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The purpose of this study is to propose a solution to this problem.

Design/methodology/approach

The current study identifies relevant literature and provides a review of big data adoption in libraries. It also presents a step-by-step guide for the development of a BDA platform using the Apache Hadoop Ecosystem. To test the system, an analysis of library big data using Apache Pig, which is a tool from the Apache Hadoop Ecosystem, was performed. It establishes the effectiveness of Apache Hadoop Ecosystem as a powerful BDA solution in libraries.

Findings

It can be inferred from the literature that libraries and librarians have not taken the possibility of big data services in libraries very seriously. Also, the literature suggests that there is no significant effort made to establish any BDA architecture in libraries. This study establishes the Apache Hadoop Ecosystem as a possible solution for delivering BDA services in libraries.

Research limitations/implications

The present work suggests adapting the idea of providing various big data services in a library by developing a BDA platform, for instance, providing assistance to the researchers in understanding the big data, cleaning and curation of big data by skilled and experienced data managers and providing the infrastructural support to store, process, manage, analyze and visualize the big data.

Practical implications

The study concludes that Apache Hadoops’ Hadoop Distributed File System and MapReduce components significantly reduce the complexities of big data storage and processing, respectively, and Apache Pig, using Pig Latin scripting language, is very efficient in processing big data and responding to queries with a quick response time.

Originality/value

According to the study, there are significantly fewer efforts made to analyze big data from libraries. Furthermore, it has been discovered that acceptance of the Apache Hadoop Ecosystem as a solution to big data problems in libraries are not widely discussed in the literature, although Apache Hadoop is regarded as one of the best frameworks for big data handling.

Details

Digital Library Perspectives, vol. 40 no. 2
Type: Research Article
ISSN: 2059-5816

Keywords

Article
Publication date: 5 April 2024

Xiaohong Shi, Ziyan Wang, Runlu Zhong, Liangliang Ma, Xiangping Chen and Peng Yang

Smart contracts are written in high-level programming languages, compiled into Ethereum Virtual Machine (EVM) bytecode, deployed onto blockchain systems and called with the…

Abstract

Purpose

Smart contracts are written in high-level programming languages, compiled into Ethereum Virtual Machine (EVM) bytecode, deployed onto blockchain systems and called with the corresponding address by transactions. The deployed smart contracts are immutable, even if there are bugs or vulnerabilities. Therefore, it is critical to verify smart contracts before deployment. This paper aims to help developers effectively and efficiently locate potential defects in smart contracts.

Design/methodology/approach

GethReplayer, a smart contract testing method based on transaction replay, is proposed. It constructs a parallel transaction execution environment with two virtual machines to compare the execution results. It uses the real existing transaction data on Ethereum and the source code of the tested smart contacts as inputs, conditionally substitutes the bytecode of the tested smart contract input into the testing EVM, and then monitors the environmental information to check the correctness of the contract.

Findings

Experiments verified that the proposed method is effective in smart contract testing. Virtual environmental information has a significant effect on the success of transaction replay, which is the basis for the performance of the method. The efficiency of error locating was approximately 14 times faster with the proposed method than without. In addition, the proposed method supports gas consumption analysis.

Originality/value

This paper addresses the difficulty that developers encounter in testing smart contracts before deployment and focuses on helping develop smart contracts with as few defects as possible. GethReplayer is expected to be an alternative solution for smart contract testing and provide inspiration for further research.

Details

International Journal of Web Information Systems, vol. 20 no. 4
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 8 May 2023

Yumeng Hou, Fadel Mamar Seydou and Sarah Kenderdine

Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have…

Abstract

Purpose

Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as apparatuses for well-annotated and object-based collections. Hence, there is a pressing need for empowering the representation of intangible expressions, particularly embodied knowledge within its cultural context. To address this issue, the authors propose to inspect the potential of machine learning methods to enhance archival knowledge interaction with intangible cultural heritage (ICH) materials.

Design/methodology/approach

This research adopts a novel approach by combining movement computing with knowledge-specific modelling to support retrieving through embodied cues, which is applied to a multimodal archive documenting the cultural heritage (CH) of Southern Chinese martial arts.

Findings

Through experimenting with a retrieval engine implemented using the Hong Kong Martial Arts Living Archive (HKMALA) datasets, this work validated the effectiveness of the developed approach in multimodal content retrieval and highlighted the potential for the multimodal's application in facilitating archival exploration and knowledge discoverability.

Originality/value

This work takes a knowledge-specific approach to invent an intelligent encoding approach through a deep-learning workflow. This article underlines that the convergence of algorithmic reckoning and content-centred design holds promise for transforming the paradigm of archival interaction, thereby augmenting knowledge transmission via more accessible CH materials.

Article
Publication date: 15 March 2024

Florian Rupp, Benjamin Schnabel and Kai Eckert

The purpose of this work is to explore the new possibilities enabled by the recent introduction of RDF-star, an extension that allows for statements about statements within the…

Abstract

Purpose

The purpose of this work is to explore the new possibilities enabled by the recent introduction of RDF-star, an extension that allows for statements about statements within the Resource Description Framework (RDF). Alongside Named Graphs, this approach offers opportunities to leverage a meta-level for data modeling and data applications.

Design/methodology/approach

In this extended paper, the authors build onto three modeling use cases published in a previous paper: (1) provide provenance information, (2) maintain backwards compatibility for existing models, and (3) reduce the complexity of a data model. The authors present two scenarios where they implement the use of the meta-level to extend a data model with meta-information.

Findings

The authors present three abstract patterns for actively using the meta-level in data modeling. The authors showcase the implementation of the meta-level through two scenarios from our research project: (1) the authors introduce a workflow for triple annotation that uses the meta-level to enable users to comment on individual statements, such as for reporting errors or adding supplementary information. (2) The authors demonstrate how adding meta-information to a data model can accommodate highly specialized data while maintaining the simplicity of the underlying model.

Practical implications

Through the formulation of data modeling patterns with RDF-star and the demonstration of their application in two scenarios, the authors advocate for data modelers to embrace the meta-level.

Originality/value

With RDF-star being a very new extension to RDF, to the best of the authors’ knowledge, they are among the first to relate it to other meta-level approaches and demonstrate its application in real-world scenarios.

Details

The Electronic Library , vol. 42 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 17 July 2024

Siqi Yi and Soo Young Rieh

This paper aims to critically review the intersection of searching and learning among children in the context of voice-based conversational agents (VCAs). This study presents the…

Abstract

Purpose

This paper aims to critically review the intersection of searching and learning among children in the context of voice-based conversational agents (VCAs). This study presents the opportunities and challenges around reconfiguring current VCAs for children to facilitate human learning, generate diverse data to empower VCAs, and assess children’s learning from voice search interactions.

Design/methodology/approach

The scope of this paper includes children’s use of VCAs for learning purposes with an emphasis on conceptualizing their VCA use from search as learning perspectives. This study selects representative works from three areas of literature: children’s perceptions of digital devices, children’s learning and searching, and children’s search as learning. This study also includes conceptual papers and empirical studies focusing on children from 3 to 11 because this age spectrum covers a vital transitional phase in children’s ability to understand and use VCAs.

Findings

This study proposes the concept of child-centered voice search systems and provides design recommendations for imbuing contextual information, providing communication breakdown repair strategies, scaffolding information interactions, integrating emotional intelligence, and providing explicit feedback. This study presents future research directions for longitudinal and observational studies with more culturally diverse child participants.

Originality/value

This paper makes important contributions to the field of information and learning sciences and children’s searching as learning by proposing a new perspective where current VCAs are reconfigured as conversational voice search systems to enhance children’s learning.

Details

Information and Learning Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-5348

Keywords

Open Access
Article
Publication date: 9 May 2024

Nabila As’ad, Lia Patrício, Kaisa Koskela-Huotari and Bo Edvardsson

The service environment is becoming increasingly turbulent, leading to calls for a systemic understanding of it as a set of dynamic service ecosystems. This paper advances this…

1219

Abstract

Purpose

The service environment is becoming increasingly turbulent, leading to calls for a systemic understanding of it as a set of dynamic service ecosystems. This paper advances this understanding by developing a typology of service ecosystem dynamics that explains the varying interplay between change and stability within the service environment through distinct behavioral patterns exhibited by service ecosystems over time.

Design/methodology/approach

This study builds upon a systematic literature review of service ecosystems literature and uses system dynamics as a method theory to abductively analyze extant literature and develop a typology of service ecosystem dynamics.

Findings

The paper identifies three types of service ecosystem dynamics—behavioral patterns of service ecosystems—and explains how they unfold through self-adjustment processes and changes within different systemic leverage points. The typology of service ecosystem dynamics consists of (1) reproduction (i.e. stable behavioral pattern), (2) reconfiguration (i.e. unstable behavioral pattern) and (3) transition (i.e. disrupting, shifting behavioral pattern).

Practical implications

The typology enables practitioners to gain a deeper understanding of their service environment by discerning the behavioral patterns exhibited by the constituent service ecosystems. This, in turn, supports them in devising more effective strategies for navigating through it.

Originality/value

The paper provides a precise definition of service ecosystem dynamics and shows how the identified three types of dynamics can be used as a lens to empirically examine change and stability in the service environment. It also offers a set of research directions for tackling service research challenges.

Details

Journal of Service Management, vol. 35 no. 6
Type: Research Article
ISSN: 1757-5818

Keywords

Article
Publication date: 4 October 2022

Akanksha Jaiswal, Santoshi Sengupta, Madhusmita Panda, Lopamudra Hati, Verma Prikshat, Parth Patel and Syed Mohyuddin

The COVID-19 pandemic and technological advancements have enabled employees to telework. Referring to this emerging phenomenon, the authors aim to examine how employees' levels of…

2175

Abstract

Purpose

The COVID-19 pandemic and technological advancements have enabled employees to telework. Referring to this emerging phenomenon, the authors aim to examine how employees' levels of trust in management mediated by psychological well-being impact their performance as they telework. Deploying the theoretical lens of person-environment misfit, the authors also explore the role of technostress in the trust-wellbeing-performance relationship.

Design/methodology/approach

The data was collected from 511 full-time service sector employees across Indian organizations through a structured survey questionnaire. The proposed moderation-mediation model for this study was tested using structural equation modeling and bootstrapping method.

Findings

Structural equation modeling results indicate that trust in management significantly impacts employee performance while teleworking. While psychological well-being was observed as a significant mediator, technostress played the moderator role in the trust-performance relationship. The moderated-mediation effect of psychological well-being in the trust-performance relationship was stronger when technostress was low and weaker when technostress was high.

Research limitations/implications

The authors extend the person-environment misfit theory in the context of telework, highlighting the role of technostress that may impact the trust-wellbeing- performance relationship in such work settings.

Practical implications

The study informs leaders and managers on balancing delicate aspects such as employee trust and well-being that significantly impact performance as they telework. The authors also highlight the critical role of managers in respecting employees' personal and professional boundaries to alleviate technostress.

Originality/value

The authors make a novel theoretical contribution to the emerging literature on teleworking by examining the trust-psychological wellbeing-performance link and the role of technostress in this relationship.

Details

International Journal of Manpower, vol. 45 no. 1
Type: Research Article
ISSN: 0143-7720

Keywords

Article
Publication date: 29 March 2024

Sihao Li, Jiali Wang and Zhao Xu

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information…

Abstract

Purpose

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information carried by BIM models have made compliance checking more challenging, and manual methods are prone to errors. Therefore, this study aims to propose an integrative conceptual framework for automated compliance checking of BIM models, allowing for the identification of errors within BIM models.

Design/methodology/approach

This study first analyzed the typical building standards in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage, and a data extraction method based on the Dynamo is designed to obtain checking data files. After that, a matching algorithm is devised to express the logical rules of knowledge graph triples, resulting in automated compliance checking for BIM models.

Findings

Case validation results showed that this theoretical framework can achieve the automatic construction of domain knowledge graphs and automatic checking of BIM model compliance. Compared with traditional methods, this method has a higher degree of automation and portability.

Originality/value

This study introduces knowledge graphs and natural language processing technology into the field of BIM model checking and completes the automated process of constructing domain knowledge graphs and checking BIM model data. The validation of its functionality and usability through two case studies on a self-developed BIM checking platform.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 23 August 2023

Robert Randolph, Eric Kushins and Prachi Gala

Despite similarities, research across family business and business advising forwards contradictory conclusions when considering family business advising. The authors seek to…

Abstract

Purpose

Despite similarities, research across family business and business advising forwards contradictory conclusions when considering family business advising. The authors seek to integrate these literature and in doing so uncover both the hurdles facing family business advisors attempting to adapt tools developed in corporate advising to the family business context as well as the potential for greater integration of these streams in ways that contribute to both family business and advising research and practice.

Design/methodology/approach

Primary data were collected both in the form of a survey questionnaire and website marketing content. In the survey, 47 family business advisors evaluated the distinctiveness of their family business clients across structural, cognitive and relational social capital dimensions. Motivated by unexpected findings, a content analysis of advisor websites uncovered specific marketing themes that illustrate the divides between family business advising and scholarship.

Findings

Family business advisors reliably acknowledge structural and cognitive social capital as preeminently characterizing the distinctiveness of their family business clients. Expanding on this, the authors’ findings suggest that the urgency signaled in advisor marketing via their websites may inspire tactics misaligned with the long-term time horizon typically characterizing family businesses strategy.

Originality/value

The few family business advising studies that exist predominantly consider post-hoc evaluation of advising by family business clients. The primary data the authors collect are unique in the literature in that the data detail how family business advisors perceive and engage with potential clients.

Details

Journal of Family Business Management, vol. 14 no. 2
Type: Research Article
ISSN: 2043-6238

Keywords

1 – 10 of 41