An Approach to Dynamic Fusion of the Knowledge Maps of an Activities Process

International Journal of Information Systems and Supply Chain Management

Zahra

Mohammed

et al. 2021

Self Cite

In today’s context (competition and knowledge economy), ML and KM on the supply chain level have received increased attention aiming to determine long and short-term success of many companies. However, demand forecasting with maximum accuracy is absolutely critical to invest in various ﬁelds, which places the knowledge extract process in high demand. In this paper, we propose a hybrid approach of prediction into a demand forecasting process in supply chain based on the one hand, on the processes analysis for best professional knowledge for required competencies. And on the other hand, the use of different data sources by supervised learning to improve the process of acquiring explicit knowledge, maximizing the efficiency of the demand forecasting, and comparing the obtained efficiency results. Therefore, the results reveal that the practices of KM should be considered as the most important factors affecting the demand forecasting process in supply chain. The classifier performance is examined by using a confusion matrix based on their Accuracy and Kappa value.

Section: Km Processes Componentsmentioning

confidence: 99%

Forecasting Supply Chain Demand Approach Using Knowledge Management Processes and Supervised Learning Techniques

International Journal of Information Systems and Supply Chain Management

Zahra

Mohammed

et al. 2021

Self Cite

“…A knowledge map is a useful technique to reach this goal. Knowledge mapping, considered an instrument which indicates the places where knowledge is located (among some citizens, organizational units, or sources of information) and how to conduct acquisition, access to and transfer of this knowledge (Brahami et al ., 2015). In the other words, knowledge mapping is a process by which organizations can identify and categorize knowledge assets within their organization – people, processes, content, and technology.…”

Section: Literature Review/background and Related Workmentioning

confidence: 99%

“…The first focuses on classification by process and on the classification by domains that organize the knowledge around the subjects, objects, or purposes of common interest that have been identified in the organization. The critical knowledge mapping method, BKMDM, is classified in the latest approach (Brahami et al ., 2015; Brahami, 2016). The latter (BKMDM) proposes in parallel to formalize the strategy and to identify strategic competencies and other items by achieving a criticality analysis of knowledge domains with the trades.…”

Section: Proposed Approachmentioning

confidence: 99%

The relationship between knowledge mapping and the open innovation process: the case of education system

Matta

2019

AIEDAM

In an increasingly competitive economic environment, innovation has become an invaluable asset to the organization and for effective knowledge management (KM). Nowadays, organizations are knowledge based and their success and survival depend on creativity, diversity, and innovation. A knowledge map is a vital tool for better KM and innovation. To this effect, the innovation processes on KMin education system through knowledge transfer activities will facilitate the shift from teaching as knowledge transmission to teaching as learning facilitation. In this context, we present a new approach based on, the one hand, the critical knowledge mapping being based on an extraction work of the expert knowledge and on the other hand, the description of the conceptual framework design which allows one to exploit and integrate knowledge capitalized and external knowledge by the open innovation process. In addition, this practice makes it possible to examine how KM, in particular, the knowledge mapping, can be used to establish the flow of the internal and external information in order to increase the efficiency of creativity and invention.

“…Theremainderofthepaperisorganizedasfollows.Section2isanoverviewofrelatedworks concerning some background information on text mining and Knowledge Management concept. Section 3 describes our proposed model that combines KDD for text mining and Knowledge management concept in particular BKMDM method principal (Brahami et al, 2013) in order to improvetheknowledgeBooleanmappingofSEMEP.Sections4presentsanddiscussexperimental resultsobtainedfortheimprovementofknowledgeBooleanmappingbyexploitingminedprediction rules.Finally,thelastsectionisabouttheconclusionandfuturework.…”

Section: Introductionmentioning

confidence: 99%

Towards a Model to Improve Boolean Knowledge Mapping by Using Text Mining and Its Applications

International Journal of Information Retrieval Research

Mohammed

Matta

2020

The textual document set has become an important and rapidly growing information source especially for the health sector. Many efforts are made to cope with medical text explosion and to obtain useful knowledge from it, and also predict diseases and anticipate the cure. Text mining and natural language processing are fast-growing areas of research, with numerous applications in medical, pharmaceutical, and scientific avenues. Text knowledge management oversees the storage, capture, and sharing of knowledge encoded in hospital reports, primarily chronic disease records. The main objective of this article is to present the design of a model to improve Boolean knowledge mapping by knowledge extraction from medical reports dealing with epidemiological surveillance. This model that the authors have developed in this article is conducted in two major phases. The first is the preprocessing phase that produces an index of words which is the vector binary representation in order to generate the categorization model based on the Boolean modeling inspired by the Boolean knowledge management guided by data mining (BKMDM) method. In the second phase, with the data mining techniques, they exploit the vector binary representation to improve and refine the Boolean knowledge mapping of SEMEP. They examine experiment performance of the proposed model and compare it with other results such as tacit and explicit knowledge of SEMEP. Finally, knowledge mapping can be used for decision making by health specialists or can help in research topics for improving the health system.