Augmenting knowledge-based medical systems with tacit healthcare expertise: towards an intelligent tacit knowledge acquisition info-structure

2002 ◽  
Author(s):  
Yu-N Cheah ◽  
Syed Sibte Raza Abidi
Keyword(s):  
Knowledge Acquisition ◽  
Tacit Knowledge ◽  
Medical Systems ◽  
Knowledge Based

Research on Knowledge Discovery and Stock Forecasting of Financial News Based on Domain Ontology

2019 ◽  
Vol 18 (03) ◽  
pp. 953-979 ◽  
Author(s):  
Lingling Zhang ◽  
Minghui Zhao ◽  
Zili Feng
Keyword(s):  
Knowledge Acquisition ◽  
Knowledge Discovery ◽  
Tacit Knowledge ◽  
Explicit Knowledge ◽  
Academic Research ◽  
Online News ◽  
Domain Ontology ◽  
General Mechanism ◽  
Financial News ◽  
Knowledge Reasoning

In the era of big data, how to obtain useful knowledge from online news and utilize it as an important basis to make investment decision has become the hotspot of industrial and academic research. At present, there have been research and practice on explicit knowledge acquisition from news, but tacit knowledge acquisition is still under exploration. Based on the general mechanism of domain knowledge, knowledge reasoning, and knowledge discovery, this paper constructs a framework for discovering tacit knowledge from news and applying the knowledge to stock forecasting. The concrete work is as follows: First, according to the characteristics of financial field and the conceptual cube, the conceptual structure of industry–company–product is constructed, and the framework of domain ontology is put forward. Second, with the construction of financial field ontology, the financial news knowledge management framework is proposed. Besides, with the application of attributes in ontology and domain rules extracted from news text, the knowledge reasoning mechanism of financial news is constructed to achieve financial news knowledge discovery. Finally, news knowledge that reflects important information about stock changes is integrated into the traditional stock price forecasting model and the newly proposed model performs well in the empirical analysis of polyester industry.

scholarly journals A META-TOOL TO SUPPORT THE DEVELOPMENT OF KNOWLEDGE ENGINEERING METHODOLOGIES AND PROJECTS

2012 ◽  
Vol 22 (08) ◽  
pp. 1055-1083
Author(s):  
JOSÉ ELOY FLÓREZ ◽  
JAVIER CARBÓ ◽  
FERNANDO FERNÁNDEZ
Keyword(s):  
Knowledge Acquisition ◽  
Ad Hoc ◽  
Knowledge Engineering ◽  
Domain Specific ◽  
Advantages And Disadvantages ◽  
Knowledge Based ◽  
Combined Application ◽  
Processing Information ◽  
Knowledge Acquisition Methods ◽  
Applied Knowledge

Knowledge-based systems (KBSs) or expert systems (ESs) are able to solve problems generally through the application of knowledge representing a domain and a set of inference rules. In knowledge engineering (KE), the use of KBSs in the real world, three principal disadvantages have been encountered. First, the knowledge acquisition process has a very high cost in terms of money and time. Second, processing information provided by experts is often difficult and tedious. Third, the establishment of mark times associated with each project phase is difficult due to the complexity described in the previous two points. In response to these obstacles, many methodologies have been developed, most of which include a tool to support the application of the given methodology. Nevertheless, there are advantages and disadvantages inherent in KE methodologies, as well. For instance, particular phases or components of certain methodologies seem to be better equipped than others to respond to a given problem. However, since KE tools currently available support just one methodology the joint use of these phases or components from different methodologies for the solution of a particular problem is hindered. This paper presents KEManager, a generic meta-tool that facilitates the definition and combined application of phases or components from different methodologies. Although other methodologies could be defined and combined in the KEManager, this paper focuses on the combination of two well-known KE methodologies, CommonKADS and IDEAL, together with the most commonly-applied knowledge acquisition methods. The result is an example of the ad hoc creation of a new methodology from pre-existing methodologies, allowing for the adaptation of the KE process to an organization or domain-specific characteristics. The tool was evaluated by students at Carlos III University of Madrid (Spain).

scholarly journals Tacit knowledge, as a source of competitiveness: case study

2021 ◽  
pp. 27-33
Author(s):  
Patricia RIVERA-ACOSTA ◽  
Rosa Elia MARTÍNEZ-TORRES ◽  
Maricela OJEDA-GUTIÉRREZ
Keyword(s):  
Tacit Knowledge ◽  
Family Business ◽  
Raw Materials ◽  
Talent Management ◽  
Formal Training ◽  
Case Study Methodology ◽  
Knowledge Based ◽  
The Family ◽  
Study Methodology

In the society of the XXI century it is generally accepted that a new intangible resource of organizations is knowledge, in addition to the other existing resources: human, capital, raw materials and equipment. This is particularly true in a knowledge-based society and economy, where knowledge has become an invaluable medium for all organizations, particularly businesses. The objective of this paper is to make a diagnosis to describe how to apply knowledge management in the family business Campechanas la Escondida de la Trinidad. This project is based on a case study methodology, with a descriptive type of research; the collection of information uses as instruments with a qualitative approach, observation and interviewing. The results obtained show a dependence on the tacit knowledge possessed by bakers who apply in the artisanal process, in addition to family members, lack human talent management, formal training and innovation, which has limited their competitiveness.

OPGEN: A System to Identify and Evaluate Potential Applications of Knowledge Based Systems

1992 ◽  
Author(s):  
Samir Rohatgi ◽  
James H. Oliver ◽  
Stuart S. Chen
Keyword(s):  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Knowledge Based Systems ◽  
The Core ◽  
Knowledge Based ◽  
Evaluation Functions ◽  
Potential Applications ◽  
Computer Based ◽  
Suitable System ◽  
Overall Effectiveness

Abstract This paper describes the development of OPGEN (Opportunity Generator), a computer based system to help identify areas where a knowledge based system (KBS) might be beneficial, and to evaluate whether a suitable system could be developed in that area. The core of the system is a knowledge base used to carry out the identification and evaluation functions. Ancillary functions serve to introduce and demonstrate KBS technology to enhance the overall effectiveness of the system. All aspects of the development, from knowledge acquisition through to testing are presented in this paper.

TQM and Knowledge Management

2017 ◽  
pp. 236-263 ◽  
Author(s):  
Luis Mendes
Keyword(s):  
Knowledge Management ◽  
Quality Management ◽  
Total Quality Management ◽  
Tacit Knowledge ◽  
Explicit Knowledge ◽  
Quality Management System ◽  
Conversion Process ◽  
Total Quality ◽  
Knowledge Based ◽  
Strategic Approach

During the last decades, both quality management and Knowledge Management (KM) have undergone a progressive evolution and have been associated with keywords such as competition, creativity, or innovativeness. Moreover, literature points to several commonalities between Total Quality Management (TQM) and Knowledge Management. The main aim of this chapter is to highlight the main commonalities, and to analyze how organizations may benefit from a dual strategic approach based on TQM and KM principles, and how integrated knowledge-based quality management system may benefit the “conversion” process of tacit knowledge into explicit knowledge, as well as the knowledge transfer/sharing process.

Fuzzy Methods in Data Mining

2011 ◽  
pp. 907-912 ◽  
Author(s):  
Eyke Hüllermeier
Keyword(s):  
Data Mining ◽  
Knowledge Acquisition ◽  
Control Function ◽  
Knowledge Discovery In Databases ◽  
Knowledge Based ◽  
Automated Learning ◽  
Long Time ◽  
Basic Ideas ◽  
Inference Techniques ◽  
Tools And Techniques

Tools and techniques that have been developed during the last 40 years in the field of fuzzy set theory (FST) have been applied quite successfully in a variety of application areas. A prominent example of the practical usefulness of corresponding techniques is fuzzy control, where the idea is to represent the input-output behaviour of a controller (of a technical system) in terms of fuzzy rules. A concrete control function is derived from such rules by means of suitable inference techniques. While aspects of knowledge representation and reasoning have dominated research in FST for a long time, problems of automated learning and knowledge acquisition have more and more come to the fore in recent years. There are several reasons for this development, notably the following: Firstly, there has been an internal shift within fuzzy systems research from “modelling” to “learning”, which can be attributed to the awareness that the well-known “knowledge acquisition bottleneck” seems to remain one of the key problems in the design of intelligent and knowledge-based systems. Secondly, this trend has been further amplified by the great interest that the fields of knowledge discovery in databases (KDD) and its core methodical component, data mining, have attracted in recent years. It is hence hardly surprising that data mining has received a great deal of attention in the FST community in recent years (Hüllermeier, 2005). The aim of this chapter is to give an idea of the usefulness of FST for data mining. To this end, we shall briefly highlight, in the next but one section, some potential advantages of fuzzy approaches. In preparation, the next section briefly recalls some basic ideas and concepts from FST. The style of presentation is purely non-technical throughout; for technical details we shall give pointers to the literature.

Tacit Knowledge in Geographical Context

2004 ◽  
Author(s):  
Meric S. Gertler
Keyword(s):  
Technological Change ◽  
Tacit Knowledge ◽  
Central Component ◽  
Michael Polanyi ◽  
Codified Knowledge ◽  
Industrial Economics ◽  
Geographical Concentration ◽  
Knowledge Based ◽  
Current Period ◽  
Prime Determinant

It has now become commonplace to refer to the current period of capitalist development as the era of the ‘knowledge-based’ (OECD 1996) or ‘learning’ (Lundvall and Johnson 1994) economy. No matter which label one prefers, the production, acquisition, absorption, reproduction, and dissemination of knowledge is seen by many as the fundamental characteristic of contemporary competitive dynamics. Long before this parlance became popular, scholars had expressed a deep interest in distinguishing between different types of knowledge. Philosophers of knowledge such as Ryle (1949) and Michael Polanyi (1958; 1966) anticipated later developments in social constructivist thought by enunciating what was for them a crucial distinction between knowledge that could be effectively expressed using symbolic forms of representation—explicit or codified—and other forms of knowledge that defied such representation—tacit knowledge (see Reber 1995; Barbiero n.d.). Within the field of innovation studies and technological change, and especially since the publication of Nonaka and Takeuchi’s The Knowledge- Creating Company (1995), the distinction between tacit and codified knowledge has been accorded great significance. However, in characteristically prescient fashion Nelson and Winter (1982) in their classic work had already made extensive use of the concept, which informed their analysis of organizational routines within an evolutionary perspective on technological change. In drawing attention to this concept, these authors helped revive widespread interest in the earlier work of Michael Polanyi, to the point where tacit knowledge has come to be recognized as a central component of the learning economy, and a key to innovation and value creation. Moreover, tacit knowledge is also acknowledged as a prime determinant of the geography of innovative activity, since its central role in the process of learning through interacting tends to reinforce the local over the global. For a growing number of scholars, this explains the perpetuation and deepening of geographical concentration in a world of expanding markets, weakening borders, and ever cheaper and more pervasive communication technologies. Recently, tacit knowledge has received considerable attention within the field of industrial economics (see for e.g. Cowan, David, and Foray 2000; Johnson, Lorenz, and Lundvall 2002), where a process of critical re-examination has begun.

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