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Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions.

This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS.

The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules.

This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

Despite ongoing research into archival metadata standards, digital archives are unable to effectively represent records in their appropriate contexts. This study aims to propose a knowledge graph that depicts the diverse relationships between heterogeneous digital archive entities.

This study introduces and describes a method for applying knowledge graphs to digital archives in a step-by-step manner. It examines archival metadata standards, such as Records in Context Ontology (RiC-O), for characterising digital records; explains the process of data refinement, enrichment and reconciliation with examples; and demonstrates the use of knowledge graphs constructed using semantic queries.

This study introduced the 97imf.kr archive as a knowledge graph, enabling meaningful exploration of relationships within the archive’s records. This approach facilitated comprehensive record descriptions about different record entities. Applying archival ontologies with general-purpose vocabularies to digital records was advised to enhance metadata coherence and semantic search.

Most digital archives serviced in Korea are limited in the proper use of archival metadata standards. The contribution of this study is to propose a practical application of knowledge graph technology for linking and exploring digital records. This study details the process of collecting raw data on archives, data preprocessing and data enrichment, and demonstrates how to build a knowledge graph connected to external data. In particular, the knowledge graph of RiC-O vocabulary, Wikidata and Schema.org vocabulary and the semantic query using it can be applied to supplement keyword search in conventional digital archives.

The scientific community shares a heritage of knowledge generated by several different fields of research. Identifying how scientific interest evolves is relevant for recording and understanding research trends and society’s demands.

This article presents SciBR-M, a novel method to identify scientific interest evolution from bibliographic material based on Formal Concept Analysis. The SciBR-M aims to describe the thematic evolution surrounding a field of research. The method begins by hierarchically organising sub-domains within the field of study to identify the themes that are more relevant. After this organisation, we apply a temporal analysis that extracts implication rules with minimal premises and a single conclusion, which are helpful to observe the evolution of scientific interest in a specific field of study. To analyse the results, we consider support, confidence, and lift metrics to evaluate the extracted implications.

The authors applied the SciBR-M method for the Educational Data Mining (EDM) field considering 23 years since the first publications. In the digital libraries context, SciBR-M allows the integration of the academy, education, and cultural memory, in relation to a study domain.

Cultural changes lead to the production of new knowledge and to the evolution of scientific interest. This knowledge is part of the scientific heritage of society and should be transmitted in a structured and organised form to future generations of scientists and the general public.

The method, based on Formal Concept Analysis, identifies the evolution of scientific interest to a field of study. SciBR-M hierarchically organises bibliographic material to different time periods and explores this hierarchy from proper implication rules. These rules permit identifying recurring themes, i.e. themes subset that received more attention from the scientific community during a specific period. Analysing these rules, it is possible to identify the temporal evolution of scientific interest in the field of study. This evolution is observed by the emergence, increase or decrease of interest in topics in the domain. The SciBR-M method can be used to register and analyse the scientific, cultural heritage of a field of study. In addition, the authors can use the method to stimulate the process of creating knowledge and innovation and encouraging the emergence of new research.

The purpose of this paper is to review ontologies and data models currently in use for augmented reality (AR) applications, in the cultural heritage (CH) domain, specifically in an urban environment. The aim is to see the current trends in ontologies and data models used and investigate their applications in real world scenarios. Some special cases of applications or ontologies are also discussed, as being interesting enough to merit special consideration.

A search using Google Scholar, Scopus, ScienceDirect and IEEE Xplore was done in order to find articles that describe ontologies and data models in AR CH applications. The authors identified the articles that analyze the use of ontologies and/or data models, as well as articles that were deemed to be of special interest.

This review found that CIDOC-CRM is the most popular ontology closely followed by Historical Context Ontology (HiCO). Also, a combination of current ontologies seems to be the most complete way to fully describe a CH object or site. A layered ontology model is suggested, which can be expanded according to the specific project.

This study provides an overview of ontologies and data models for AR CH applications in urban environments. There are several ontologies currently in use in the CH domain, with none having been universally adopted, while new ontologies or extensions to existing ones are being created, in the attempt to fully describe a CH object or site. Also, this study suggests a combination of popular ontologies in a multi-layer model.

Using the data set about the restaurants from different countries and their customer's feedback, the purpose of this paper is to address the following issues: in the restaurant industry, how have user behavior and preferences changed during the COVID-19 restrictions period, how did these changes influence the performance of recommendation algorithms and which methods can be proposed to improve the quality of restaurant recommendations in a lockdown scenario.

To assess changes in user behavior and preferences, quantitative and qualitative data analysis was performed to assess the changes in user behavior and preferences. The authors compared the situation before and during the COVID-19 restrictions period. To evaluate the performance of restaurant recommendation systems in a non-stationary setting, the authors tested state-of-the-art collaborative filtering algorithms. This study proposes and investigates a filtering-based approach to improve the quality of recommendation algorithms for a lockdown scenario.

This study revealed that during the COVID-19 restrictions period, the average rating values and the number of reviews have changed. The experimental study confirmed that: the performance of all state-of-the-art recommender systems for the restaurant industry has significantly degraded during the COVID-19 restrictions period; and the accuracy and the stability of restaurant recommendations in non-stationary settings may be improved using the sliding window and post-filtering methods.

The authors propose two novel methods: the sliding window and closed restaurants post-filtering method based on the CatBoost classification model. These methods can be applied to classical collaborative recommender algorithms and increase the value of metrics under non-stationary conditions. These methods can be helpful for developers of recommender systems and massive aggregators of restaurants and hotels. Thus, it benefits both the app end-user and business owners because users honestly rate restaurants when they receive good recommendations and do not downgrade because of external factors.

To the best of the authors’ knowledge, this paper provides the first extensive and multifaceted experimental study of the impact of COVID-19 restrictions on the effectiveness of restaurant recommendation systems in different countries. Two novel methods to tackle restaurant recommendations' performance degradation are proposed and validated.

利用关于不同国家餐厅及其顾客反馈的数据, 我们探索了以下问题：(i) 在餐饮行业, 用户行为和偏好在COVID-19限制期间如何改变, (ii) 这些变化如何影响推荐算法的性能, 以及 (iii) 可以提出哪些方法来改进封锁情景下的餐厅推荐质量。

为了评估用户行为和偏好的变化, 本研究进行了定量和定性数据分析, 对比了COVID-19限制期前后的情况。为了评估非稳态环境中餐厅推荐系统的性能, 我们测试了最先进的协同过滤算法。我们提出并研究了一种基于过滤的方法, 以提高封锁情景下推荐算法的质量。

研究发现, 在COVID-19限制期间, 平均评分和评论数量发生了变化。实验研究证实：(i) 在COVID-19限制期间, 所有最先进的餐厅行业推荐系统的性能显著下降; (ii) 使用滑动窗口和后过滤方法可以改进非稳态环境下餐厅推荐的准确性和稳定性。

我们提出了两种新方法：基于CatBoost分类模型的关闭餐厅后过滤和滑动窗口方法。这些方法可以应用于经典的协同过滤推荐算法, 并在非稳态条件下提高指标值。这些方法对于推荐系统的开发者和大规模餐厅和酒店聚合平台都有帮助。因此, 这对于应用的最终用户和企业主都有好处, 因为当用户得到良好的推荐时, 他们会诚实地对餐厅进行评价, 而不会因为外部因素降低评分。

本文首次提供了COVID-19限制对不同国家餐厅推荐系统有效性影响的广泛多方面的实验研究, 并提出和验证了两种解决餐厅推荐性能下降问题的新方法。

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

This paper aims at explore the intervening role of servant leadership in tourism businesses' outcomes, in the context of travel agencies. Drawing on servant leadership theory, the authors develop a multimediation model exploring the relationships between servant leadership and person–job fit, work–life balance, work engagement, innovative work behavior and job crafting.

Using SmartPLS3, data collected from 942 travel agencies operating in Egypt, a questionnaire was used to obtain data on how travel agency employees envisage their organization’s adoption of servant leadership, person–job fit, job crafting, work–life balance, work engagement and innovative work behavior.

The authors show that servant leadership correlates positively with person–job fit, work–life balance, work engagement, innovative work behavior and job crafting, while job crafting correlates positively with work–life balance, work engagement and innovative work behaviors. The partial mediating roles of both job crafting and person–job fit in the link between servant leadership and work–life balance, and the partial mediating role of work engagement in the link between servant leadership and innovative work behaviors.

Up to date, research on the effects of servant leadership on person–job fit, job crafting, work–life balance, work engagement and innovative work behavior has been inadequate. In terms of contextual applicability, an empirical investigation of the relationship between these factors in travel agencies is not available. By empirically examining these relationships in the context of Egyptian travel agencies, the current study has bridged a gap in the tourism and hospitality literature, human resources management and organizational behavior literature.

本文旨在探讨仆人式领导在旅行社背景下对旅游企业成果的干预作用。借鉴仆人式领导理论, 我们开发了一个多重中介模型, 探索仆人式领导与人-工作契合度、工作-生活平衡、工作投入、创新工作行为和工作重塑之间的关系。

使用 SmartPLS3, 从在埃及运营的 942 家旅行社收集的数据, 使用问卷调查获取有关旅行社员工如何设想他们的组织采用仆人式领导、人-工作匹配、工作重塑、工作与生活平衡、工作参与和和 创新工作行为。

我们表明, 仆人式领导与人-工作契合度、工作-生活平衡、工作投入、创新工作行为和工作重塑呈正相关, 而工作重塑与工作-生活平衡、工作投入和创新工作行为呈正相关。工作重塑和个人-工作在仆人式领导与工作-生活平衡之间的联系中起部分中介作用, 工作投入在仆人式领导与创新工作行为之间的联系中起部分中介作用。

该研究进行了一些开创性的检查。迄今为止, 关于仆人式领导对人-工作契合度、工作重塑、工作-生活平衡、工作投入和创新工作行为的影响的研究还不够充分。就情境适用性而言, 尚无对旅行社中这些因素之间关系的实证研究。通过在埃及旅行社的背景下对这些关系进行实证检验, 当前的研究弥合了旅游和酒店文献、人力资源管理和组织行为文献中的空白。

El objetivo de este artículo es explorar el papel que desempeña el liderazgo de servicio en los resultados de las empresas turísticas, en el contexto de las agencias de viajes. Basándonos en la teoría del liderazgo de servicio, desarrollamos un modelo de mediación múltiple que explora las relaciones entre el liderazgo de servicio y la adecuación de la persona al trabajo, el equilibrio entre el trabajo y la vida personal, el compromiso laboral, el comportamiento laboral innovador y el diseño proactivo del puesto de trabajo.

Con SmartPLS3 se analizaron datos recopilados de 942 agencias de viajes que operan en Egipto mediante un cuestionario con el que se obtuvo información sobre cómo los empleados de agencias de viajes prevén que su organización adopte el liderazgo de servicio, el ajuste persona-trabajo, el diseño proactivo del puesto de trabajo, el equilibrio entre el trabajo y la vida personal, el compromiso laboral y el comportamiento laboral innovador.

Mostramos que el liderazgo de servicio se correlaciona positivamente con el ajuste persona-trabajo, el equilibrio entre el trabajo y la vida personal, el compromiso laboral, el comportamiento laboral innovador y el diseño proactivo del puesto de trabajo, mientras que el diseño del puesto de trabajo se correlaciona positivamente con el equilibrio entre la vida laboral y personal, el compromiso laboral y los comportamientos laborales innovadores. Mostramos también el papel mediador parcial del diseño proactivo del puesto de trabajo y del ajuste persona-trabajo, en el vínculo entre el liderazgo de servicio y el equilibrio entre el trabajo y la vida personal, asi como el papel mediador parcial del compromiso laboral en el vínculo entre el liderazgo de servicio y los comportamientos laborales innovadores.

Hasta la fecha, la investigación sobre los efectos del liderazgo de servicio en la adecuación de la persona al trabajo, el diseño proactivo del puesto de trabajo, el equilibrio entre el trabajo y la vida personal, el compromiso laboral y el comportamiento laboral innovador ha sido insuficiente. En términos de aplicabilidad contextual, no se disponía de una investigación empírica de la relación entre estos factores en las agencias de viajes. Al examinar empíricamente estas relaciones en el contexto de las agencias de viajes egipcias, el presente estudio cubre un vacío en la literatura sobre turismo y hostelería, gestión de recursos humanos y comportamiento organizacional.

This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.

Select eight representative IS journals as data sources, extract the theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by conducting theory co-occurrence network analysis, diversity measure and evolution analysis.

As a young and vibrant discipline, IS has been continuously absorbing and internalizing external theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of some kernel theories, the interdisciplinarity of IS appears to be decreasing and gradually converging into a few neighboring disciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting from a theory centered one to a technology centered one.

This study helps to understand the evolution of the interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.

This study identifies the kernel theories in IS research, measures the interdisciplinarity of IS based on the evolution of the co-occurrence network of theory source disciplines and reveals the paradigm shift being happening in IS.

This study explores how open innovation (OI) can be instrumental for entrepreneurs in sensing and seizing entrepreneurial opportunities in small and medium enterprises (SMEs). This study also illustrates how OI can help SMEs overcome the liability of smallness.

This is exploratory research using an inductive, multiple-case study approach. This study capitalizes on five in-depth case studies of European SMEs to explore a phenomenon using replication logic and provide a robust basis for theory building.

This study presents a holistic view of the OI process in SMEs and illustrates the crucial role of entrepreneurs. The study provides a better understanding of how OI can help entrepreneurs sense and seize entrepreneurial opportunities by envisioning venture ideas and implementing business model innovation through the management of innovation partners.

The study emphasizes two critical roles of entrepreneurs in implementing OI in SMEs. First, the entrepreneur can be the instigator of strategic change, and second, he/she can orchestrate the innovation network. The findings emphasize that OI helps avoid knowledge corridors at the venture idea stage, leading to a (re)structuring of the business model and the emergence of a network of innovation partners, which should be managed hands-on. This study discusses in detail the two crucial roles of entrepreneurs.

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.