A Semantic Query Tool for Evaluation Expert Knowledge Base

2012 ◽  
Author(s):  
Xiaoming Zhang ◽  
Hongxia Ma ◽  
Dong Fu
Keyword(s):  
Knowledge Base ◽  
Expert Knowledge ◽  
Semantic Query ◽  
Query Tool

Automatic Ontology Learning from Multiple Knowledge Sources of Text

2018 ◽  
Vol 14 (2) ◽  
pp. 1-21 ◽  
Author(s):  
B Sathiya ◽  
T.V. Geetha
Keyword(s):  
Knowledge Base ◽  
Web Pages ◽  
Knowledge Sources ◽  
Statistical Measure ◽  
Ontology Learning ◽  
Web Page ◽  
Semantic Query ◽  
Probabilistic Knowledge ◽  
Discovery Algorithms ◽  
Different Sources

The prime textual sources used for ontology learning are a domain corpus and dynamic large text from web pages. The first source is limited and possibly outdated, while the second is uncertain. To overcome these shortcomings, a novel ontology learning methodology is proposed to utilize the different sources of text such as a corpus, web pages and the massive probabilistic knowledge base, Probase, for an effective automated construction of ontology. Specifically, to discover taxonomical relations among the concept of the ontology, a new web page based two-level semantic query formation methodology using the lexical syntactic patterns (LSP) and a novel scoring measure: Fitness built on Probase are proposed. Also, a syntactic and statistical measure called COS (Co-occurrence Strength) scoring, and Domain and Range-NTRD (Non-Taxonomical Relation Discovery) algorithms are proposed to accurately identify non-taxonomical relations(NTR) among concepts, using evidence from the corpus and web pages.

scholarly journals Beyond the discipline : A metadisciplinary approach for the didactics of communication design

2018 ◽  
Vol 3 (6) ◽  
pp. 021-051 ◽  
Author(s):  
Gimapero Dalai ◽  
Berta Martini ◽  
Luciano Perondi ◽  
Monica Tombolato
Keyword(s):  
Knowledge Base ◽  
Expert Knowledge ◽  
Educational Design ◽  
Communication Design ◽  
Basic Set ◽  
Epistemological Status

We reflect specifically on the curriculum for bachelor’s level program in communication design. We propose a model of education which we define as “metadisciplinary” and which is grounded on the acquisition of competences rather than the acquisition of specific contents. Our objective is to show how a metadisciplinary didactic model can benefit from the weak epistemological status of the knowledge base of communication design. According to the idea that didactics can be treated as a science of design, we propose a model of educational design based on a metadisciplinary stance. First we describe two fundamental aspects of the model proposed: (1) the development of habitus of thought and action and (2) the distributed and collective nature of expert knowledge. Next, we discuss the notion of curriculum architecture. Finally, we describe a basic set of metadisciplinary competences that we have identified for students in the field of communication design.

An experimental transformation of a large expert knowledge base

1982 ◽  
Vol 6 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Robert N. Goldberg ◽  
Sholom M. Weiss
Keyword(s):  
Knowledge Base ◽  
Expert Knowledge

scholarly journals Selecting a Strategy for Determining the Combine Harvester Parameter Settings

2020 ◽  
Vol 30 (1) ◽  
pp. 60-75
Author(s):  
Lyudmila V. Borisova ◽  
Inna N. Nurutdinova ◽  
Valeriy P. Dimitrov ◽  
Andrey K. Tugengold
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Performance Indicators ◽  
Intelligent System ◽  
Expert Knowledge ◽  
External Environment ◽  
Suggested Approach ◽  
Expert Information ◽  
The Matrix ◽  
Combine Harvester

Introduction.The article deals with adjusting the parameter settings of a combine harvester working bodies. For adjustment of complex hierarchical multilevel systems, the intellectual methods based on fuzzy expert information are used. The incoming quantitative, qualitative and evaluation information is analyzed when adjusting the combine harvester. The different types of uncertainty in considering semantic spaces of external environment factors and regulated parameters of the machine cause the application of logical and linguistic approach and mathematical apparatus of fuzzy logic for determining the optimal initial settings. The complex system of interrelations between parameters, indicators of quality of harvest, and factors of external environment causes the necessity to adjust the parameters of combine working elements in the process of harvesting. This function is performed by the correction unit in the intelligent decision support system. In the present article, the questions of creating a knowledge base for correcting adjustment parameters in cases when there are deviations of values of harvesting quality indicators from normative values are considered in detail. Materials and Methods. Interrelations between performance indicators and regulated parameters are established by empirical rules obtained through the collection and analysis of expert information. To optimize the mechanism of intellectual information system output and reduce the time of decision making, there is a necessity to establish the relevance of used knowledge base rules. To solve this problem, theoretical and game approaches are used, concepts of the matrix of performance indicators and the matrix of risks of making an inefficient decision are used. Results. An example of choosing a strategy of searching for an adequate response to the fault of the harvesting indices in the form of “losses of feeble grain with chaff” has been given. The choice of fault response strategies on the basis of Laplace criterion, expectedvalue criterion, and Savage test used for decision-making in “games with nature” has been considered. The method of the decision-making process in the problem under consideration with the application of the mentioned criteria were illustrated, the analysis of the obtained results was carried out. Discussion and Conclusion. The suggested approach substantially increases performance of the unit of intelligent system updating. It allows structuring the expert knowledge base and establishing an optimal sequence of application of production rules; this provides efficiency of the updating process of the adjustable harvester parameters and also reduces the time for decision-making. This approach can be used while solving the problems of updating technological adjustments in different technical systems and devices.

scholarly journals PROTECTION OF SCIENTIFIC AND EDUCATIONAL RESOURCES IN INFORMATION AND LIBRARY SYSTEMS

2019 ◽  
Vol 2 (2) ◽  
pp. 121-128
Author(s):  
M. A. Rakhmatullaev ◽  
Sh. B. Normatov
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Base ◽  
Information Technologies ◽  
Expert Knowledge ◽  
Fuzzy Model ◽  
Educational Resources ◽  
Electronic Library ◽  
Unauthorized Access ◽  
Degree Of Protection ◽  
Corporate Network

Introduction. The authors of the article highlight the results of research on the development of methods and tools for ensuring the information security of scientific and educational resources in information library systems and corporate information networks. The analysis of the state of the problem and the existing approaches on this topic are given too.Materials and Methods. The approach justifies the need to protect scientific resources from unauthorized access and the use of fuzzy logic to solve the problem. As a model and solution method, a fuzzy model correspondences is proposed, which makes it possible to comprehensively solve the problem of identifying threats in the event of a situation, as well as provide recommendations on how to eliminate them. For the formation of a knowledge base, experts are involved who determine the functions of belonging to knowlege base “Situation — Threats — Actions to eliminate the threats”.Results. The research results are being implemented as part of the ARMAT++ information library system of the corporate network of electronic libraries of 63 Uzbekistan universities for the protection of scientific and educational information from unauthorized access. Testing of the methods, programs of the subsystem and the expert knowledge base are carried out on the basis of information and resource centers under the project “Virtual electronic library of the Tashkent University of Information Technologies named after Muhammad Al-Khorezmi and its five branches”.Discussion and Conclusions. The use of the apparatus of fuzzy logic for the formation of a knowledge base of the “Situation — Threats — Actions to eliminate the threats” type in information library systems significantly increases the degree of protection of valuable information resources from unauthorized access.

scholarly journals Sistem Pakar Pemupukan Kelapa Sawit Menggunakan Metode Forward Chaining

2017 ◽  
Vol 16 (2) ◽  
Author(s):  
Yusuf Priyandari ◽  
Roni Zakaria ◽  
Abdan Syakura
Keyword(s):  
Knowledge Base ◽  
Oil Palm ◽  
Expert Knowledge ◽  
Nutrient Deficiency ◽  
Inference Engine ◽  
Knowledge Bases ◽  
Influential Factor ◽  
Forward Chaining ◽  
Fresh Fruit Bunches ◽  
Visual Basic Application

<em>Oil palm smallholders require knowledge of fertilization because the fertilization is an influential factor in the productivity of fresh fruit bunches. On the other hand, the oil palm smallholders generally don’t have fertilizer expertise and they face a difficulty in determining good fertilization (good in type, dosage, time and manner) based on various literatures. Therefore, a simple application that can provide recommendations for palm oil fertilization is developed. The recommendations are based on expert knowledge that have been written in various literatures. Like an expert system, the application is designed by compiling knowledge base, constructing an inference engine and creating a prototype. The knowledge bases, that are facts and rules, are prepared using rule-based reasoning approach, the inference engine is compiled using forward chaining methods and the prototype is made using a visual basic application in a spreadsheet application. The application design uses facts of plant varieties, phases or age of plants, soil types, nutrient deficiency in soil and plants, rainfall, fertilizer content, and nutrient properties (synergies or antagonist) on fertilizers. The Applications made capable of providing fertilization recommendations by conducting forward chaining based on data-given facts and rules that have been made on the knowledge base.</em>

scholarly journals INFORMATION SYSTEM FOR EVALUATION OF THE STATE OF INTOXICATION OF THE ORGANISM BASED ON THE BAYES NETWORK

2021 ◽  
Vol 3 (163) ◽  
pp. 144-151
Author(s):  
O. Moyseenko
Keyword(s):  
Decision Making ◽  
Information System ◽  
Expert System ◽  
Knowledge Base ◽  
Expert Knowledge ◽  
Experimental Testing ◽  
Postoperative Treatment ◽  
Formal Representation ◽  
Medical Systems ◽  
Electrode Potentials

An expert system is a computer program that simulates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field. It is a program that emulates the interaction a user might have with a human expert to solve a problem. The end user provides input by selecting one or more answers from a list or by entering data. An Expert System is a problem solving and decision making system based on knowledge of its task and logical rules or procedures for using knowledge. Both the knowledge and the logic are obtained from the experience of a specialist in the area. This paper considers approaches to building a knowledge base for medical systems. In developing the knowledge base of the information system, Bayesian networks were chosen as the basis for the decision-making model by type of patient pathology. This choice was due to the availability of these networks the ability to work with uncertain knowledge used in the diagnosis of diseases, in choosing the optimal course of treatment and subsequent prediction of patients. In addition, they offer the most adequate formal representation of inaccurate knowledge, as they are the result of a synthesis of statistical methods of data analysis and artificial intelligence. The presence of hydrosulfide ion intoxication (HS-intoxication), divalent iron ion intoxication (Fe-intoxication), the patient's absence of pathology and the value of Ag2S and Pt electrode potentials were selected as nodes of this network. Based on the accumulated experience of monitoring the condition of patients during their postoperative treatment (data obtained in collaboration with Ivano-Frankivsk National Medical University), as well as experimental data, conditional probabilities of values that can take the readings of the electrodes were established. Experimental testing of the adequacy of the proposed and implemented model was performed on an array of data from potentiometric measurements of patients' biomaterial. The prediction made by the network was taken as the node that had the highest probability of being in a state that indicates the presence of a pathology. Comparison of the results of the network with data obtained by other methods showed their convergence in 85% of cases. Thus, the developed network can be used to facilitate the process of diagnosing the presence and type of intoxication of the patient and is included in the information system for monitoring the patient's condition.

Automatic Intelligent Data Analysis

2009 ◽  
pp. 1-17
Author(s):  
Martin Spott ◽  
Detlef Nauck
Keyword(s):  
Data Analysis ◽  
Knowledge Base ◽  
Expert Knowledge ◽  
Soft Constraints ◽  
Intelligent Data Analysis ◽  
Automatic Data ◽  
Analysis Methods ◽  
Automatic Data Analysis ◽  
Data Analysis Methods ◽  
Fuzzy Knowledge

This chapter introduces a new way of using soft constraints for selecting data analysis methods that match certain user requirements. It presents a software platform for automatic data analysis that uses a fuzzy knowledge base for automatically selecting and executing data analysis methods. In order to support business users in running data analysis projects the analytical process must be automated as much as possible. The authors argue that previous approaches based on the formalisation of analytical processes were less successful because selecting and running analytical methods is very much an experience-led heuristic process. The authors show that a system based on a fuzzy knowledge base that stores heuristic expert knowledge about data analysis can successfully lead to automatic intelligent data analysis.

Pest Activity Prognosis in the Rice Field

2007 ◽  
pp. 763-768 ◽  
Author(s):  
N. Arbaiy
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Rice Field ◽  
Expert Knowledge ◽  
Life Stage ◽  
Control Measures ◽  
Specific Knowledge ◽  
Main Components ◽  
Activity Prognosis ◽  
Consultation Session

In crops management, it is important to estimate the damage effected by pests since the degree of damage will determine the level of pest activity. Pest activity usually involves their life stage and its presence in the field. In addition, pest management in crops is a crucial problem and may yield losses if it is not handled properly. Consequently a forecasting tool is needed to predict the level of pest activity. This is important so that an early treatment or action can be applied before more damage to the plant occurs. Accordingly, the fuzzy expert system may facilitate the user through a consultation session in order to forecast the pest activity in the rice field. A set of questions will be asked to help users diagnose their given symptom in order to infer such a conclusion. Figure 1 shows the main components of an expert system including inference engine, expert, knowledge base, working memory, and user interface. The consultation performed by the expert system also involves fuzzy logic to deal with the natural and uncertainty data. Besides, all the information and knowledge about the pests, treatment control measures and prevention steps are managed in the specific knowledge base created in the system. This system is able to educate and inform the farmers and smallholders about pests and their activities in the rice field.

Pest Plant Disease Prevention and Identification System Using Certainty Factor Method

2018 ◽  
Vol 7 (3.2) ◽  
pp. 763 ◽  
Author(s):  
Robbi Rahim ◽  
Nuning Nurna Dewi S ◽  
M Zamroni ◽  
Lilla Puji Lestari ◽  
Muh Barid Nizarudin Wajdi ◽  
...  
Keyword(s):  
Expert System ◽  
Disease Prevention ◽  
Expert Systems ◽  
Knowledge Base ◽  
Plant Disease ◽  
Expert Knowledge ◽  
Identification System ◽  
Certainty Factor ◽  
Factor Method

Diseases in plants are something that can happen to many plants either caused by pests or other factors, the disease in plants can be detected based on the symptoms that appear on the plant before spreading to all plants, to recognize the symptoms and types of diseases contained in plants require plant experts or also by applying expert systems with expert knowledge base applied to the system by using certain methods such as certainty factor method. Expected results with the availability of this expert system to the user can help many users to detect diseases in plants.  

Sign in / Sign up

Export Citation Format

Share Document