Knowledge Warehouse Research Articles

Knowledge Management in Serbian SMEs: Key Factors of Influence on Internal and External Business Performances

This study investigates the pivotal role of knowledge management (KM) in Serbian small- and medium-sized enterprises (SMEs), highlighting its impact on both the internal dynamics and external business performance of a company. Addressing the unique socio-economic and cultural context of the Serbian business environment, this research study explores how effectively KM practices can streamline business processes, enhance decision making, and foster more significant outputs. This study includes a sample of 370 companies, conducted during the period of the initial 6 months of 2023, by measuring the influence of knowledge management factors within the process of generating revenue and on decreasing operating costs. Drawing on previous theoretical research provided by different experts, followed by a quantitative analysis performed through principal component analysis (PCA), this study identifies critical factors of influence for KM adoption and exploitation in Serbian SMEs. This study offers insights into the interplay between knowledge acquisition, formation, application, warehousing, and knowledge transfer. Findings suggest that from an external perspective, the process capabilities of a company for acquiring and formatting knowledge have a positive influence on business performance, while the technological capabilities of a company for knowledge warehousing, sharing, and formatting produce the same effect but from an internal business perspective.

REDIRECT: Mapping Drug Prescriptions and Evidence from Biomedical Literature.

To enhance their practice, healthcare professionals need to cross-link various usage recommendations provided by heterogeneous vocabularies that must be retrieved and integrated conjointly. This is the aim of the Knowledge Warehouse / K-Ware platform. It enables establishing relevant bridges between different knowledge sources (structured vocabularies, thesaurus, ontologies) expressed in the semantic web standard languages (i.e. SKOS, OWL, RDF). This poster presents the strategy applied in K-Ware to hide the different aspects of linking literals with medical entities encoded in these knowledge sources to fetch some publications abstracts from Pubmed.

Framework for Developing a Knowledge Warehouse Towards a Resilient Semiconductor Assembly and Testing Firm

Framework for Developing a Knowledge Warehouse Towards a Resilient Semiconductor Assembly and Testing Firm

Information integration framework for a public–private partnership system of an urban railway transit project (Part A: System architecture)

The public–private partnership (PPP) financing mode has developed rapidly since its introduction into China's municipal engineering construction. However, successful PPP projects are rare due to the lack of a scientific information integration system. This study proposes an information integration framework of the risk and reward mechanism for urban rail transit (URT) PPP projects on the basis of data and knowledge warehouses. The proposed information integration framework is the core decision-making mechanism of URT project financing and further operation in China in recent decades. It can provide a supporting reference for URT project management in other countries.

Long-term effectiveness of group-based diabetes self-management on glycosylated haemoglobin for people with type 2 diabetes in community: a protocol of systematic review and meta-analysis

IntroductionThe rapid rise in the prevalence of diabetes has a negative impact on patients’ quality of life. Diabetes self-management group education is cost-effective and efficient for patients to control blood...

Towards Knowledge Warehousing: Application to Smart Housing

The terms data, information and knowledge should not be treated as synonyms in any context. In fact, a hierarchical order between these entities exists where data become information and information become knowledge. Massive amounts of data are analysed everyday in order to extract valuable knowledge to support decision making. However, the size of the extracted knowledge compromises the speed of reasoning and exploitation of the latter. In this paper, we propose the paradigm of knowledge warehousing to store and analyse big amounts of knowledge through online knowledge processing and knowledge mining techniques. Our proposal is supported by an original knowledge warehouse framework and a case study for the smart housing technology. A multi-agent system built on a knowledge warehouse architecture is illustrated where each agent has a knowledge base about his assigned task. The paradigm is expected to be applicable for other knowledge tasks and domains as well.

Towards knowledge warehousing: application to smart housing

Towards knowledge warehousing: application to smart housing

A Method of Interest Degree Mining Based on Behavior Data Analysis

Based on big data, this paper starts from the behavior data of users on social media, and studies and explores the core issues of user modeling under personalized services. Focusing on the goal of user interest modeling, this paper proposes corresponding improvement measures for the existing interest model, which has great difference in interest description among different users and it is difficult to find the user interest change in time. For the above problems, this paper takes user-generated content and user behavior information as the analysis object, and uses natural language processing, knowledge warehouse, data fusion and other methods and techniques to numerically analyze user interest mining based on text mining and multi-source data fusion. We propose a user interest label space mapping method to avoid data sparse problem caused by too many dimensions in interest analysis. At the same time, we propose a method to extract and blend the long-term and short-term interests, and realize the comprehensive evaluation of interests. In the analysis of the big data phase, the user preference social property application preference value law, it is expected to achieve user Internet social media application preference data mining from the perspective of big data.

Using a Digital Personal Learning Network Assignment to Teach Social Curation and Lifelong Learning in Marketing

As the use of social media continues to grow in practice and as an academic discipline, so too does the need for marketing students (and faculty) to develop and maintain a career-focused and current knowledge warehouse of information that is optimized to their own unique life situation—hence, the creation and use of what is described as a digital personal learning network or “PLN.” This article describes a proven assignment framework, requiring students to build their own digital PLN, using widely available RSS newsfeed tools such as Feedly and Twitter Lists. Student feedback is offered to support the effectiveness of this approach and suggestions are made regarding other courses that could benefit from being taught with the support of a PLN-based assignment.

RESEARCH ON THE FRAMEWORK OF THE SMART CONSERVATION MANAGEMENT SYSTEM FOR THE HISTORIC CITY FUZHOU

Abstract. Historic cities, especially inhabited historic cities, are a special type of cultural heritage. Because of the expanding intension and extension of urban heritage, the rapid urbanization and the various stakeholders, the historic cities become much more complex nowadays. The need of GIS-based information systems for historic cities has never been greater. This paper introduces the research on the framework of the Smart Conservation Management System for the Historic City Fuzhou. It is an effort to explore an informatization way for historic cities. The needs of urban heritage itself, and the needs of different stakeholders should be respected. This system follows the principle of authenticity and integrity conservation, the coordination of conservation and sustainable development, the consideration of stakeholders, ease of use, extensibility, and security. The database should be fit for the construction of knowledge warehouse, be easy to collect and renew information. The module should be able to apply easily in everyday use situations, support smart decision making for the users. It is hoped that the research and the system will be referential for other historic cities.

A Framework for Knowledge Models Transformation: A Step Towards Knowledge Integration and Warehousing

An intelligent decision support system should based on a knowledge warehouse (KW). A KW gathers knowledge initially expressed in different formalisms and therefore heterogeneous. Consequently, the KW building process requires knowledge homogenisation. This paper deals with this main issue; it introduces a three-layer architecture for a KW; more precisely, it focuses on the first layer architecture called Knowledge Acquisition and Transformation. This layer aims to transform heterogeneous knowledge models into the MOT (Modeling with Object Types) semi-formal language [Paquette, G (2002). Knowledge and Skills Modeling: A Graphical Language for Designing and Learning. Sainte-Foy: University of Quebec Press (in French).] that we have selected as a pivot knowledge model. For this transformation step, first, we design four meta-models; one for MOT and one for each of the three explicit knowledge models, namely, decision tree, association rules and clustering. Secondly, we define 15 transformation rules that we formalise in ATL (Atlas Transformation Language). Finally, we exemplify the knowledge transformation in order to show its usefulness for the KW building process.

Design of a hybrid intelligent system for the management of flood disaster risks

The frequency of occurrence and intensity of floods is a huge threat to environment, human existence, critical infrastructure and economy. Flood risk assessments depend on probabilistic approaches and suffer from non-existence of appropriate indices of acceptable risk, dearth of information and pieces of knowledge for explicit view and understanding of the characteristics and severity level of flood hazard. This paper proposes a hybridized intelligent framework comprising fuzzy logic (FL), neural network and genetic algorithm for clustering and visualization of flood data, prediction and classification of flood risks severity level. A multidimensional knowledge model of flood incidence using star, snowflake and facts constellation schemas was proposed for the knowledge warehouse. A six-layered adaptive neuro-fuzzy inference system implementing mamdani’s inference mechanism was design to evaluate input features based on fuzzy rules held in the multidimensional data model. The system is aimed at predicticting and classifying flood risk severity levels. The perception of emergency risk management is very important in modern society. Therefore, this work provides a framework for the practical applications of data mining techniques and tools to emergency risk management. The work would assist to identify locations with significant flood risk.

Which barriers hinder a successful digital transformation in small and medium-sized municipalities in a federal system?

This paper presents a proposal for reconciliation between the warehouse of legal documents created during legislation and Knowledge Warehouse that is dedicated to assisting both citizens and public officers in the procedural legal rules of Public Administration in Hungary. The Knowledge Warehouse contains several thousand detailed rules that describe how to manage and handle life events of citizens. This description can be considered as generic legal cases within legal procedures of authorities. The citizens trigger specific instances of the generic ones. The evolving Knowledge Warehouse main purpose is to enable citizens to get their specific legal cases started either through Web on the Government Portal or with the help of public officers. The Knowledge Warehouse will be extended by ontologies and semantic search capabilities. An Integrated System for Supporting of Codification will be created in an on-going project that will serve as sound basis for the National Warehouse of Legal Rules. The National Warehouse pursues the prescription of MetaLex legal standards in the case of representation of electronic legal documents. The two Warehouse are strongly coupled to each other. However, the syntactic and semantic structure of both differs profoundly. The representation of e-documents within the National Warehouse is in line with ELI, the European Legislation Identifier, even the ontologies and attached semantic description concentrates on the legal documents structural elements and their interpretation. The Knowledge Warehouse focuses on ontologies of life events and procedures of authorities to leverage semantic searching. The proposed solution tries to reconcile and integrate the two differing approaches.

Semantic Reconciliation between two Different Aspects of Law

This paper presents a proposal for reconciliation between the warehouse of legal documents created during legislation and Knowledge Warehouse that is dedicated to assisting both citizens and public officers in the procedural legal rules of Public Administration in Hungary. The Knowledge Warehouse contains several thousand detailed rules that describe how to manage and handle life events of citizens. This description can be considered as generic legal cases within legal procedures of authorities. The citizens trigger specific instances of the generic ones. The evolving Knowledge Warehouse main purpose is to enable citizens to get their specific legal cases started either through Web on the Government Portal or with the help of public officers. The Knowledge Warehouse will be extended by ontologies and semantic search capabilities. An Integrated System for Supporting of Codification will be created in an on-going project that will serve as sound basis for the National Warehouse of Legal Rules. The National Warehouse pursues the prescription of MetaLex legal standards in the case of representation of electronic legal documents. The two Warehouse are strongly coupled to each other. However, the syntactic and semantic structure of both differs profoundly. The representation of e-documents within the National Warehouse is in line with ELI, the European Legislation Identifier, even the ontologies and attached semantic description concentrates on the legal documents structural elements and their interpretation. The Knowledge Warehouse focuses on ontologies of life events and procedures of authorities to leverage semantic searching. The proposed solution tries to reconcile and integrate the two differing approaches.

Development of methodology for data and knowledge warehouse design in computer systems for intellectual data processing

At present, when developing data warehouses and knowledge of computer systems, it is not possible to use one end-to-end methodology, suitable for collective work and knowledge sharing. Such methodology should be understandable and objective from the point of view of the provability and validity of models at all stages of research and design work. The object of research is development of a methodology for designing efficient data warehouses and knowledge of modern computer systems for intellectual data processing. During the development of the methodology, the categorical-ontological approach developed by the author as a metalanguage of modeling and a means for verification of the design process and its results was used. In this case, the generic ontological model is mathematically rigorous, by imposing constraints on the objects and morphisms of category theory on the concepts and relationships that are presented. As a result of the development and application of this methodology, the semantic and linguistic barriers that arise between the members of the project team in the design of data and knowledge warehouses of computer systems have been overcome. Using a categorical-ontological approach to modeling and design makes it possible to formally substantiate the subjective results of knowledge engineering and use the objects of category theory in the form of design patterns at a high level of abstraction.

Entity-relation modeling and discovery for smart search

Nowadays, by connecting the mobile networks, Internet of Things and the sensor networks to the Internet, the cyberspace has expanded to a ubiquitous space of human beings, machines and things. Combining with the technology of big data, the traditional search engines are evolving into their next generation—big search (or smart search). En- tity-relation modeling and discovery are the key techniques to fulfill the vision of smart search. Approaches to model the entities and their relations in large scale by knowledge graph and knowledge warehouse, and ways to discovery new enti- ties and the relations between them in the cyberspace are discussed.

MOT Knowledge Model Integration Rules for Knowledge Warehousing

A knowledge warehousing process aims to build an intelligent decision support system. It collects, homogenizes, integrates and stores knowledge for a decision-making process. In this paper, we are interested in knowledge integration. More accurately, we propose an integration process for knowledge homogenized/modeled according to the MOT (Modeling with Object Types) knowledge model. This integration process consists of three ordered steps based on the type of schemas to integrate and their similarity. For this process, we define five integration rules based on semantic relationships between elements of MOT knowledge models, and then we develop an algorithm using these integration rules.

Reconceptualizing the U.S. strategic food safety system

Purpose To introduce an innovative communicative platform to be constructed to facilitate food hazard communications as new policy initiatives shift the direction of food safety management from reaction to prevention.. Design/methodology/approach Literature from economics and management is examined for concepts that would yield potential solutions to accomplish the purpose. Findings An innovative synthesis of four interrelated structural elements – resource, identity, standard, and knowledge (RISK) – is proposed as the framework for hazard communication. Practical implications Exchanges of food hazard knowledge and information among diverse stakeholders (consumers, suppliers, public agencies) in a complex environment requires an information architecture, a “knowledge warehouse,” that explicitly organizes interactive elements in social networks to facilitate knowledge communication among those stakeholders. Originality/value Drawing upon the management literature and merging it with concepts from economics yields unique perspectives, creating value and contributing to a more effective and efficient market-based food safety system.

Knowledge-Driven Decision Support System Based on Knowledge Warehouse and Data Mining by Improving Apriori Algorithm with Fuzzy Logic

Knowledge-Driven Decision Support System Based on Knowledge Warehouse and Data Mining by Improving Apriori Algorithm with Fuzzy Logic

Integration of Web Services with E-Learning for Knowledge Society

The study aims of creating a knowledge society (KS) through e-learning (EL) with the support of web services. EL system with its elements is the matter of discussion at the beginning of the study. For effective EL system, integration of web services with EL system is essential which is emphasized in the paper. Web 2.0 services such as blogs promote the content creation, assessment and evaluation, wikis makes the user enable of creating editable contents in the form of highly searchable knowledge-bases. Group work, Question & Answer (Q & A) sessions are performed by social networking and discussion forums. RSS feeds, Tags, Podcasts and Videocasts are considered as supporting services to speed up the knowledge management process. Web 3.0 services can apply artificial intelligence (AI) technique to speed up the teaching/learning process. The integration is expected to create the KS and the global knowledge warehouse