Knowledge maps: A systematic literature review and directions for future research

Managing knowledge loss: a systematic literature review and future research directions

Purpose

Job market shifts, such as workforce mobility and aging societies, cause the exit of knowledgeable personnel from organizations. The ensuing knowledge loss (K-loss) has broad negative effects. This study analyzes the knowledge management literature on K-loss published from 2000 to 2021 and identifies fruitful directions for future research.

Design/methodology/approach

The authors conduct a systematic literature review of 74 peer-reviewed articles published between 2000 and 2021. These articles were retrieved from ProQuest Central, Science Direct, EBSCOhost and Emerald databases. The analysis utilizes Jesson et al.’s (2011) six principles: field mapping, comprehensive search, quality assessment, data extraction, synthesis and write-up.

Findings

Three sub-topics emerge from the systematic literature review: K-loss drivers, positive and negative impacts of K-loss and mitigation strategies. Over half of the literature addresses mitigation strategies and provides solutions for K-loss already in progress, rather than proposing preventive measures.

Research limitations/implications

This study has limitations related to the time span covered. Moreover, it focuses on articles published in refereed journals. Therefore, important contributions from conference papers, books and professional reports were excluded.

Originality/value

This research comprehensively synthesizes the K-loss literature and proposes future avenues of research to address under-investigated areas and potentially lead to theoretical and empirical advancements in the field. This study also provides suggestions for improving managerial practices.

Research trends and hotspots in climate adaptation of the agricultural system: A bibliometric analysis

Agricultural system is highly dependent on the natural environment, thus even a slight climate change can have a significant impact on it. Climate change has already caused a series of problems for the agricultural system, which makes improving climate adaptation of the agricultural system extremely important. In order to clarify the current research status, cooperation network, research hotspots and trends in climate adaptation of the agricultural system, we adopt the bibliometric method via CiteSpace to analyze the data collected from the Web of Science (WoS) Core Collection. Through the analysis of a number of publications, we found that the current research in climate adaptation of the agricultural system has entered a rapid development stage. Moreover, the United State of America (USA) is the most impactful country with the most publications in this field. In terms of institutions, the University of Leeds contributes most to the research in climate adaptation of the agricultural system. And its faculty, A. J. Dougill, is the author who contribute most to this field. By cluster analysis and burst analysis, we confirmed conceptual studies, ecologically venerable areas, and climate adaptation strategies are the hotspot in climate adaptation of the agricultural system, while impact assessment, governance and decision-making, farming system, and climate information service are the research trend in this field. This review is expected to help researchers quickly grasp the research situation in climate adaptation of the agricultural system and provide a reference for future research in this field.

SciBR-M: a method to map the evolution of scientific interest - A case study in educational data mining

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Social implications

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.

Originality/value

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.

Research trends, developments, and future perspectives in brand attitude: A bibliometric analysis utilizing the Scopus database (1944-2021)

Brand attitude has been the primary concern for corporation sustainability for a long. Studies have focused on various attributes concerning brand attitude comprising of many research articles. This study focuses on bibliometric analysis of brand attitude examining 1497 documents published for the years 1944-2021. The purpose of this study is to examine historic research trends, developments, and future conduits based on co-authorship and co-occurrence analysis using VOSviewer. The study highlights the most prolific articles containing the most productive authors and their affiliations, keywords, and influential journals, along with future research trends. The result shows that the number of publications follows a very slow trail until 2008, mildly until 2012, following which the cumulative growth in publication increased manifold. Further, results show that researchers from the United States, South Korea, and Taiwan extended many efforts to the global knowledge of literature leading other countries. The emerging hotspot keywords analysis suggests that brand avoidance, subtle, brand betrayal, consumer ethnocentrism, environmental sustainability and policy, brand activism, brand authenticity, consumer brand engagement, and brand competence are the key areas that attract researchers' attention policymakers as future research boulevards. In the case of consumers' brand attitudes, there is a scarcity of studies that investigated the consumers' implicit and explicit brand attitudes.

Knowledge graph model development for knowledge discovery in dementia research using cognitive scripting and next-generation graph-based database: a design science research approach

Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortality rate related to cognitive decline diseases, like dementia, timely information on contributing factors and knowledge discovery from evidence-based repositories is warranted. A large amount of scholarly knowledge extracted from research findings on dementia can be understood only using human intelligence for arriving at quality inferences. Due to the unstructured data presented in such a massive dataset of scientific articles available online, gaining insights from the knowledge hidden in the literature is complex and time-consuming. Hence, there is a need for developing a knowledge management model to create, query and maintain a knowledge repository of key elements and their relationships extracted from scholarly articles in a structured manner. In this paper, an innovative knowledge discovery computing model to process key findings from unstructured data from scholarly articles by using the design science research (DSR) methodology is proposed. The solution caters to a novel composition of the cognitive script of crucial knowledge related to dementia and its subsequent transformation from unstructured into a structured format using graph-based next-generation infrastructures. The computing model contains three phases to assist the research community to have a better understanding of the related knowledge in the existing unstructured research articles: (i) article collection and construction of cognitive script, (ii) generation of Cypher statements (a knowledge graph query language) and (iii) creation of graph-based repository and visualization. The performance of the computing model is demonstrated by visualizing the outcome of various search criteria in the form of nodes and their relationships. Our results also demonstrate the effectiveness of visual query and navigation highlighting its usability.

An evaluation of critical knowledge areas for managing the COVID-19 pandemic

Purpose

The ability to manage the COVID-19 pandemic is contingent upon the ability to effectively manage its heterogeneous knowledge resources. Knowledge mapping represents a great opportunity to create value by bringing stakeholders together, facilitating comprehensive collaboration and facilitating broader in-depth knowledge sharing and transfer. However, identifying and analysing critical knowledge areas is one of the most important steps when creating a knowledge map. Therefore, the purpose of this paper is to appraise the critical knowledge areas for managing COVID-19, and thereby enhance decision-making in tackling the consequences of the pandemic.

Design/methodology/approach

The methodological approach for this study is a critical literature review, covering publications on knowledge management, knowledge mapping and COVID-19. EBSCOhost, PubMed, Scopus, Science Direct, TRID, Web of Science and Wiley Online Library were searched for full text, peer-reviewed articles written in English that investigated on critical knowledge areas for managing the spread of COVID-19. After full screening, 21 articles met the criteria for inclusion and were analysed and reported.

Findings

The study revealed seven critical knowledge areas for managing the COVID-19 pandemic. These are cleaning and disinfection; training, education and communication; reporting guidance and updates; testing; infection control measures, personal protective equipment; and potential COVID-19 transmission in health and other care settings. The study developed a concept knowledge map illustrating areas of critical knowledge which decision-makers need to be aware of.

Practical implications

Providing decision-makers with access to key knowledge during the COVID-19 pandemic seems to be crucial for effective decision-making. This study has provided insights for the professionals and decision-makers identifying the critical knowledge areas for managing the COVID-19 pandemic.

Social implications

The study advances the literature on knowledge management and builds a theoretical link with the management of public health emergencies. Additionally, the findings support the theoretical position that knowledge maps facilitate decision-making and help users to identify critical knowledge areas easily and effectively.

Originality/value

This study fills gaps in the existing literature by providing an explicit representation of know-how for managing the COVID-19 pandemic. This paper uses an objective and qualitative approach by reviewing related publications, reports and guidelines in the analysis. The concept map illustrates the critical knowledge areas for managing the COVID-19 pandemic.

Knowledge graph technology application in Chinese SSCI: An example of short videos research

Thousands of new publications appear every day in bibliometric databases, so the demand for document retrieval technology is growing. Bibliometrics makes it possible to perform a quantitative analysis of text publications; however, the problem of classifying complex videos with a high level of semantics remains unsolved. Meanwhile, short-form videos gain popularity and attract more researchers. Knowledge Graph seems to be a promising technology in this area. This technology makes it possible to modernize the information search infrastructure. The experiment involved 461 short-video studies. The material for the experiment was collected from the Chinese Social Sciences Citation Index (CSSCI) database. The bibliometric method was recognized as expedient for the analysis. The keyword mapping and clustering operations were performed using the CiteSpace software. The results demonstrate that short-form video research has been popular among Chinese scientists since 2017. Short-form video research focuses on five major topics, that is, development trends, modern media convergence, video production, visual content management, and short-form videos in the public sector. The present findings may be employed in future research to collect relevant samples with exact semantic relationships. The technology is not limited to specific applications and, therefore, may be useful in any field of research.

COVID-19, consumer behavior, technology, and society: A literature review and bibliometric analysis

The COVID-19 crisis is among the most disruptive events in recent decades. Its profound consequences have garnered the interest of many studies in various disciplines, including consumer behavior, thereby warranting an effort to review and systematize the literature. Thus, this study systematizes the knowledge generated by 70 COVID-19 and consumer behavior studies in the Scopus database. It employs descriptive analysis, highlighting the importance of using quantitative methods and China and the US as research settings. Co-occurrence analysis further identified various thematic clusters among the studies. The input-process-output consumer behavior model guided the systematic review, covering several psychological characteristics and consumer behaviors. Accordingly, measures adopted by governments, technology, and social media stand out as external factors. However, revised marketing strategies have been oriented toward counteracting various consumer risks. Hence, given that technological and digital formats mark consumer behavior, firms must incorporate digital transformations in their process.

An empirical study of knowledge mapping implementation in Indonesian organizational context

Purpose

Knowledge growth is currently experiencing a very exponential increase, through a digital transformation of knowledge in the organization and the emergence of various platforms through management system content such as blogs and social media that have encouraged such growth. An employee no longer only interacts in knowledge management (KM) in his organization but can communicate and collaborate to share knowledge through these platforms widely. Much of the spread of knowledge is a challenge for organizations to manage and use their knowledge and spread knowledge and become part of the expertise possessed by employees in their organizations. For this reason, an intelligent knowledge mapping approach is needed to facilitate finding, managing and identifying knowledge owned by an organization. This paper aims to see the use of smart knowledge mapping in organizations empirically.

Design/methodology/approach

This research was conducted empirically by conducting a literature study method to compile a questionnaire and conduct a survey through purposive sampling, sampling taken from the KM and Society Indonesia community. This survey limits only to respondents who have experience in conducting knowledge mapping in an organization.

Findings

The use of data sources that have been owned by the organization and also the consideration of the use of digital footprint employees spread across the internet can be a potential to explore the knowledge resources possessed by the organization. Of course, with the support of technology through the use of artificial intelligence (AI), it is expected to be able to present a comprehensive, adaptive and objective knowledge mapping for the organization.

Practical implications

The paper provides practical implications for knowledge mapping implementation in an organization by adopting AI with considerable digital footprint employees spread across the internet.

Originality/value

This paper provides empirical information about knowledge mapping implementation in Indonesian organization.

Mapping the Knowledge Domains of Emerging Advanced Technologies in the Management of Prefabricated Construction

Emerging advanced technologies (EAT) have been regarded as significant technological innovations which can greatly improve the transforming construction industry. Given that research on EAT related to the management of prefabricated construction (MPC) has not yet been conducted, various researchers require a state-of-the-art summary of EAT research and implementation in the MPC field. The purpose of this paper is to provide a systematic literature review by analysing the selected 526 related publications in peer-reviewed leading journals during 2009–2020. Through a thorough review of selected papers from the state-of-the-art academic journals in the construction industry, EAT is recognised as the key area affecting the development of the MPC discipline. This study has value in offering original insights to summarise the advanced status quo of this field, helping subsequent researchers gain an in-depth understanding of the underlying structure of this field and allowing them to continue future research directions.

A Chinese Conceptual Semantic Feature Dataset (CCFD)

Memory and language are important high-level cognitive functions of humans, and the study of conceptual representation of the human brain is a key approach to reveal the principles of cognition. However, this research is often constrained by the availability of stimulus materials. The research on concept representation often needs to be based on a standardized and large-scale database of conceptual semantic features. Although Western scholars have established a variety of English conceptual semantic feature datasets, there is still a lack of a comprehensive Chinese version. In the present study, a Chinese Conceptual semantic Feature Dataset (CCFD) was established with 1,410 concepts including their semantic features and the similarity between concepts. The concepts were grouped into 28 subordinate categories and seven superior categories artificially. The results showed that concepts within the same category were closer to each other, while concepts between categories were farther apart. The CCFD proposed in this study can provide stimulation materials and data support for related research fields. All the data and supplementary materials can be found at https://osf.io/ug5dt/ .

Serendipity in human information behavior: a systematic review

Purpose

Serendipitous information discovery has become a unique and important approach to discovering and obtaining information, which has aroused a growing interest for serendipity in human information behavior. Despite numerous publications, few have systematically provided an overview of current state of serendipity research. Consequently, researchers and practitioners are less able to make effective use of existing achievements, which limits them from making advancements in this domain. Against this backdrop, we performed a systematic literature review to explore the world of serendipity and to recapitulate the current states of different research topics.

Design/methodology/approach

Guided by a prior designed review protocol, this paper conducted both automatic and manual search for available studies published from January 1990 to December 2020 on seven databases. A total of 207 serendipity studies closely related to human information behavior form the literature pool.

Findings

We provide an overview of distinct aspects of serendipity, that is research topics, potential benefits, related concepts, theoretical models, contextual factors and data collection methods. Based on these findings, this review reveals limitations and gaps in the current serendipity research and proposes an agenda for future research directions.

Originality/value

By analyzing current serendipity research, developing a knowledge framework and providing a research agenda, this review is of significance for researchers who want to find new research questions or re-align current work, for beginners who need to quickly understand serendipity, and for practitioners who seek to cultivate serendipity in information environments.

Visualizing risk factors of dementia from scholarly literature using knowledge maps and next-generation data models

Scholarly communication of knowledge is predominantly document-based in digital repositories, and researchers find it tedious to automatically capture and process the semantics among related articles. Despite the present digital era of big data, there is a lack of visual representations of the knowledge present in scholarly articles, and a time-saving approach for a literature search and visual navigation is warranted. The majority of knowledge display tools cannot cope with current big data trends and pose limitations in meeting the requirements of automatic knowledge representation, storage, and dynamic visualization. To address this limitation, the main aim of this paper is to model the visualization of unstructured data and explore the feasibility of achieving visual navigation for researchers to gain insight into the knowledge hidden in scientific articles of digital repositories. Contemporary topics of research and practice, including modifiable risk factors leading to a dramatic increase in Alzheimer’s disease and other forms of dementia, warrant deeper insight into the evidence-based knowledge available in the literature. The goal is to provide researchers with a visual-based easy traversal through a digital repository of research articles. This paper takes the first step in proposing a novel integrated model using knowledge maps and next-generation graph datastores to achieve a semantic visualization with domain-specific knowledge, such as dementia risk factors. The model facilitates a deep conceptual understanding of the literature by automatically establishing visual relationships among the extracted knowledge from the big data resources of research articles. It also serves as an automated tool for a visual navigation through the knowledge repository for faster identification of dementia risk factors reported in scholarly articles. Further, it facilitates a semantic visualization and domain-specific knowledge discovery from a large digital repository and their associations. In this study, the implementation of the proposed model in the Neo4j graph data repository, along with the results achieved, is presented as a proof of concept. Using scholarly research articles on dementia risk factors as a case study, automatic knowledge extraction, storage, intelligent search, and visual navigation are illustrated. The implementation of contextual knowledge and its relationship for a visual exploration by researchers show promising results in the knowledge discovery of dementia risk factors. Overall, this study demonstrates the significance of a semantic visualization with the effective use of knowledge maps and paves the way for extending visual modeling capabilities in the future.

Human resource management practices in creating a committed workforce for fostering knowledge transfer: a theoretical framework

Purpose

This paper aims to review existing literature on the role of human resource management (HRM) practices in nurturing employee’s organisational commitment (OC), which subsequently promoting knowledge transfer (KT) within an organisation and propose a conceptual framework for future empirical research.

Design/methodology/approach

An extensive review of existing literature was undertaken in an attempt to build the conceptual model for KT.

Findings

The proposed conceptual framework illustrates the role of OC as a focal mediating mechanism in fostering KT. This paper identifies “high commitment” HRM (HCHRM) (e.g. staffing, job design, training and development, performance appraisal and reward system) as the factors influencing the development of OC, which subsequently affecting KT (i.e. knowledge sharing and application). Also, this paper integrates the potential moderating roles of leader-member exchange (LMX) between HCHRM practices-OC, as well as information and communication technology support in the OC-KT linkage into the proposed framework.

Research limitations/implications

This paper presents a comprehensive view of fostering KT. However, the major limitation of this paper is that it remains at a conceptual level. Further empirical investigations would be helpful to test propositions, hence validating the proposed conceptual framework.

Practical implications

The proposed conceptual framework could serve as practical guidance for managers and/or practitioners in developing policies that will facilitate KT in business organisations.

Originality/value

While KT is often viewed as a single phenomenon, this paper considers the KT into two components (i.e, sharing and application) in accordance with the practice-based perspective on knowledge and behavioural approach to KT. In addition, the adoption of the general workplace commitment model in conceptualising KT could further validate its applicability in knowledge management research. Also, the integration of LMX as a moderator in the proposed framework could contribute to the scant research on LMX-related moderation models upon validation.

Knowledge map: a creative visual path to library guides and resources

Purpose

This paper aims to indicate that library guides seem to be unfamiliar to most students or not easy to find or use. Some improvements have been made by embedding the guides in the learning management system or promoting the guides in formal library instructional classes. Are there other ways to promote or improve the use of library guides? The author proposes an exploratory visual solution to minimize this gap between library users and library guides.

Design/methodology/approach

Guided by the cognitive load theory, the proposed solution is a knowledge map created with Freeplane. The proposal is illustrated by comparing a sample knowledge map with its content source, a subject guide in LibGuides, via three browsing paths in locating a recommended database for a particular course on the sample subject guide website.

Findings

The knowledge map can display contents in different ways and provide a simple and visual layout with direct access to the library resources, which may help lessen users’ intrinsic cognitive load, minimize extraneous load or promote germane load. The map can also be beneficial to librarians for preparing teaching materials or guides management.

Practical implications

The proposed solution can be implemented with Freeplane based on existing library guides or created from scratch.

Originality/value

The proposed solution addresses a gap in the library field, where the use of knowledge maps for library services is overlooked.

Building a digitally enhanced community of practice

Purpose

Emergency transitions from face-to-face learning environments to digitally mediated learning require robust support networks, particularly in the form of communities of practice. Digitally enhanced communities of practice (DECoP) can be created and sustained when research-based design principles are used. The purpose of this paper is to present a set of evidence-based design principles for purposeful creation of digitally enhanced communities of practice.

Design/methodology/approach

This study used integrative literature review methodology. All literature regarding DECoP was collected, analyzed and synthesized to provide a set of design principles for building DECoPs.

Findings

The analysis resulted in 26 crucial design principles and 8 desirable design principles.

Practical implications

The synthesized set of design principles provides a blueprint for designing and facilitating the development of DECoPs.

Originality/value

This unique synthesis of the DECoP literature provides practitioners with guidance in creating and nurturing a new DECoP.

Knowledge management: does gender matter? A systematic review of literature

Purpose

This paper aims to review for the first time existing research literature about the role of gender in creating, sharing and using knowledge in organizations and proposes a conceptual framework to guide future research directions.

Design/methodology/approach

Based on the systematic literature review method this study collects, synthesizes and analyses articles related to knowledge management (KM) and gender published in online databases by following a pre-defined review protocol. The paper analyses 41 papers published in peer-reviewed journals.

Findings

The role of gender in KM has been rarely addressed in KM journals and journals with specific emphasis on gender. The existing literature is fragmented, but existing research suggests that knowledge sharing might be influenced by gender. Based on the analysis and synthesis, a conceptual framework is proposed to guide further research on determining if gender matters in KM.

Research limitations/implications

Academic researchers should aim to include gender-related variables into their KM research to further explore if gender matters in KM.

Practical implications

The practical implication suggests that managers and knowledge managers should raise awareness about how stereotypes and gendered expectations about role behaviour affect how knowledge and experiences are created and shared within the organization.

Social implications

The authors believe that a better understanding of knowledge handling and gendered role expectations at the workplace could also have an impact beyond organizational boundaries.

Originality/value

The paper presents the first comprehensive systematic literature review of the article published on knowledge creation, sharing and usage and gender and provides a conceptual framework for future research.

Concept Mapping, an Effective Tool for Long-Term Memorization of Anatomy-A Quasi-Experimental Research Carried out among 1st Year General Medicine Students

This study is part of a doctoral thesis conducted at the Faculty of Psychology of Babes-Bolyai University in collaboration with the University of Medicine, both from Cluj-Napoca, Romania. The starting point of the study was based on the eternal question of the medical student—“How should I learn to manage to retain so much information?” This is how learning through conceptual maps and learning by understanding has been achieved. In the study, a number of 505 students from the Faculty of General Medicine were randomly selected and divided into groups, to observe changes in the grades they obtained when learning anatomy with the concept mapping method vs. traditional methods. Six months later, a retest was carried out to test long-term memory. The results were always in favor of the experimental group and were statistically significant (with one exception), most notably for the 6-month retesting. It was also observed that the language of teaching, different or the same as the first language, explains that exception, at least partially. Other results were taken into account, such as the distribution of bad and good grades in the two groups. Other parameters that influenced the obtained results and which explain some contradictory results in the literature are discussed. In conclusion, the use of conceptual maps is useful for most students, both for short and long-term memory.

Building Smart Knowledge Mapping Conceptual Model

Transformation in patterns of human interaction has shifted significantly in the use of the Internet, as these trends are rapidly evolving with the advent of online means for social interaction, such as social media, social networking, messaging, and so on. The transformation happens to give us challenges and opportunities to improve the quality of knowledge management undertaken by an organization. The most critical problem that in knowledge management issue is how to identify the state, ownership, and connectedness of critical knowledge in an organization visually. The studies to overcome these problems already done with a knowledge map approach, but in practice to do knowledge mapping is still done partially, either by the manual or automatic approach. Accordingly, this study aims to identify the critical components in building integrated knowledge maps from various electronic information sources that developed in the current Internet era. Through a literary study in an article that examines the map model of knowledge and by analysing smart terminology in several contexts from several kinds of literature. This study proposes a model of smart knowledge mapping conceptual model to be an initial model in developing a knowledge map that integrates various critical components.

Intellectual Capital Management and University Research Group Performance: Mediating Effects of Machiavellianism and Organisational Narcissism

The purpose of the present study is to analyse the mediating effects of organisational Machiavellianism and narcissism on the relationship between intellectual capital management (ICM) and university research group performance (URGP). The hypothesis model is tested with a sample of 288 research groups from Colombian public and private universities, since these groups are responsible for producing knowledge in the country. For the data analysis, structural equations by the partial least squares method are used. The study results show that only organisational narcissism has a mediating effect, which is partial. In conclusion, the research group must adopt narcissistic behaviours and practices, which improve the perceptions it has of its members and of its own knowledge and capacities. In this way, the group will achieve greater presence in its knowledge area and academic spaces, which leads to a better exploitation of knowledge assets and to improvements in research group performance (RGP).

Construction of personal knowledge maps for a peer-to-peer information-sharing environment

Purpose

Browsing knowledge documents in a peer-to-peer (P2P) environment is difficult because knowledge documents in such an environment are large in quantity and distributed over different peers who organize the documents according to their own views. This paper aims to propose a method for constructing a personal knowledge map for a peer to facilitate knowledge browsing and alleviate information overload in P2P environments.

Design/methodology/approach

The research presents a method for constructing a personal knowledge map. The method adopts an ontology-concept-tree-based classification algorithm to recognize a peer’s personal knowledge structure and construct a personal knowledge map, and uses a self-organizing map algorithm to cluster and visualize the knowledge documents. The correctness of the created knowledge map is evaluated with a collection of abstracts of academic papers.

Findings

The method for constructing a personal knowledge map is the main finding of this research. The evaluation shows that the created knowledge map is good in quality.

Research limitations/implications

The proposed method provides a way for P2P platforms to understand their users’ knowledge background, as well as to improve the P2P platform environment. However, the proposed method will not help a peer when he has nothing in his individual knowledge document repository (i.e. the “cold start” problem). The method also requires a relatively good ontology base for a P2P document sharing system to use the method effectively.

Originality/value

It is novel that the proposed method organizes the knowledge documents related to a peer’s knowledge background into a personal knowledge map. Moreover, the created knowledge map combines the advantages of a hierarchical display and a map display. It has values for a distributed P2P environment to facilitate users’ knowledge browsing and to alleviate information overload.

Knowledge discovery out of text data: a systematic review via text mining

Purpose

The aim of this work is to increase awareness of the potential of the technique of text mining to discover knowledge and further promote research collaboration between knowledge management and the information technology communities. Since its emergence, text mining has involved multidisciplinary studies, focused primarily on database technology, Web-based collaborative writing, text analysis, machine learning and knowledge discovery. However, owing to the large amount of research in this field, it is becoming increasingly difficult to identify existing studies and therefore suggest new topics.

Design/methodology/approach

This article offers a systematic review of 85 academic outputs (articles and books) focused on knowledge discovery derived from the text mining technique. The systematic review is conducted by applying “text mining at the term level, in which knowledge discovery takes place on a more focused collection of words and phrases that are extracted from and label each document” (Feldman et al., 1998, p. 1).

Findings

The results revealed that the keywords extracted to be associated with the main labels, id est, knowledge discovery and text mining, can be categorized in two periods: from 1998 to 2009, the term knowledge and text were always used. From 2010 to 2017 in addition to these terms, sentiment analysis, review manipulation, microblogging data and knowledgeable users were the other terms frequently used. Besides this, it is possible to notice the technical, engineering nature of each term present in the first decade. Whereas, a diverse range of fields such as business, marketing and finance emerged from 2010 to 2017 owing to a greater interest in the online environment.

Originality/value

This is a first comprehensive systematic review on knowledge discovery and text mining through the use of a text mining technique at term level, which offers to reduce redundant research and to avoid the possibility of missing relevant publications.

Means-ends based know-how mapping

Purpose

The purpose of this paper is to report on research that aims to make knowledge, and in particular know-how, more easily accessible to both academic and industrial communities, as well as to the general public. The paper proposes a novel approach to map out know-how information, so all knowledge stakeholders are able to contribute to the knowledge and expertise accumulation, as well as using that knowledge for research and applying expertise to address problems.

Design/methodology/approach

This research followed a design science approach in which mapping of the know-how information was done by the research team and then tested with graduate students. During this research, the mapping approach was continuously evaluated and refined, and mapping guidelines and a prototype tool were developed.

Findings

Following an evaluation with graduate students, it was found that the know-how maps produced were easy to follow, allowed continuous evolution, facilitated easy modification through provided modularity capabilities, further supported reasoning about know-how and overall provided adequate expressiveness. Furthermore, we applied the approach with various domains and found that it was a good fit for its purpose across different knowledge domains.

Practical implications

This paper argues that mapping out know-how within research and industry communities can further improve resource (knowledge) utilization, reduce the phenomena of “re-inventing the wheel” and further create linkage across communities.

Originality/value

With the qualities mentioned above, know-how maps can both ease and support the increase of access to expert knowledge to various communities, and thus, promote re-use and expansion of knowledge for various purposes. Having an explicit representation of know-how further encourages innovation, as knowledge from various domains can be mapped, searched and reasoned, and gaps can be identified and filled.

Visualizing the knowledge structure and evolution of big data research in healthcare informatics

BACKGROUND

In recent years, the literature associated with healthcare big data has grown rapidly, but few studies have used bibliometrics and a visualization approach to conduct deep mining and reveal a panorama of the healthcare big data field.

METHODS

To explore the foundational knowledge and research hotspots of big data research in the field of healthcare informatics, this study conducted a series of bibliometric analyses on the related literature, including papers' production trends in the field and the trend of each paper's co-author number, the distribution of core institutions and countries, the core literature distribution, the related information of prolific authors and innovation paths in the field, a keyword co-occurrence analysis, and research hotspots and trends for the future.

RESULTS

By conducting a literature content analysis and structure analysis, we found the following: (a) In the early stage, researchers from the United States, the People's Republic of China, the United Kingdom, and Germany made the most contributions to the literature associated with healthcare big data research and the innovation path in this field. (b) The innovation path in healthcare big data consists of three stages: the disease early detection, diagnosis, treatment, and prognosis phase, the life and health promotion phase, and the nursing phase. (c) Research hotspots are mainly concentrated in three dimensions: the disease dimension (e.g., epidemiology, breast cancer, obesity, and diabetes), the technical dimension (e.g., data mining and machine learning), and the health service dimension (e.g., customized service and elderly nursing).

CONCLUSION

This study will provide scholars in the healthcare informatics community with panoramic knowledge of healthcare big data research, as well as research hotspots and future research directions.