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Knowledge-Based Knowledge Elicitation [chapter]

1989 Studies in Computer Science and Artificial Intelligence  
These knowledge bases are used in addition to the already acquired knowledge to trigger specific elicitation methods by an analysis of incompleteness and inconsistency of the existing knowledge in the  ...  knowledge bases (AKBs) are integrated in the system to guide the employment of different knowledge elicitation methods (interview techniques, protocol analysis, semantic text analysis and learning mechanisms  ...  The aim of this paper is an introduction to the method of knowledge-based knowledge elicitation through several elicitation methods in a hybrid knowledge acquisition tool.  ... 
doi:10.1016/b978-0-444-87321-7.50017-x fatcat:qa72tighdzc5vf3wrg5bysw5oa

Model-based Strategic Knowledge Elicitation

J. Pedro Mendes
2016 Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management  
The present study aims to design and to explain the strategic orientation model in Iran's knowledge-based companies.  ...  The statistical population consists of 19 experts of intensive knowledge-based companies in Iran's Science and Technology Park, benefited from considerable experience and expertise in directing their startups  ... 
doi:10.5220/0006082102280234 dblp:conf/ic3k/Mendes16 fatcat:dfummoyzjzh4vdjxb4kqt23mcm

Enterprise Knowledge Based Software Requirements Elicitation

Aurelijus Morkevičius, Saulius Gudas
2011 Information Technology and Control  
The paper presents an approach for the enterprise knowledge based software requirements elicitation.  ...  requirements model, and a Semantics of Business Vocabulary and Business Rules (SBVR) standard as a formal background for elicited software requirements.  ...  Enterprise Knowledge Requirements elicitation is recognized as one of the most critical, knowledge-intensive activities of software development [34] ; poor execution of elicitation will almost guarantee  ... 
doi:10.5755/j01.itc.40.3.626 fatcat:goy4zzjhsjdvnpa3wwrrjtaf4e

Ontology-Based Knowledge Elicitation: An Architecture [chapter]

Marcello Montedoro, Giorgio Orsi, Licia Sbattella, Roberto Tedesco
2012 Lecture Notes in Computer Science  
of the acquired information; analysis and dissemination of such knowledge to all decisional levels, appropriately adapting it to the user's function and context.  ...  , of event flow within the business processes; extraction of synthetic knowledge from these information sources, possibly in terms of a common, semantic data model; automatic interpretation and integration  ...  : An Architecture Ontology-based Knowledge Elicitation: An Architecture G.  ... 
doi:10.1007/978-3-642-31739-2_9 fatcat:tl4ekbhrufcsvie2qrzyiatrua

Eliciting knowledge and transferring it effectively to a knowledge-based system

B.R. Gaines, M.L.G. Shaw
1993 IEEE Transactions on Knowledge and Data Engineering  
However, the elicitation of expert knowledge and its effective transfer to a useful knowledge-based system is complex and involves a diversity of activities.  ...  The knowledge acquisition bottleneck impeding the development of expert systems is being alleviated by the development of computer-based knowledge acquisition tools.  ...  in the development of the knowledge base transfer facilities.  ... 
doi:10.1109/69.204087 fatcat:5gbvvokyqvhwbburaxwlabsgae

PoKE: A Prompt-based Knowledge Eliciting Approach for Event Argument Extraction [article]

Jiaju Lin, Qin Chen
2022 arXiv   pre-print
Eliciting knowledge from pre-trained language models via prompt-based learning has shown great potential in many natural language processing tasks.  ...  In this paper, we present a novel prompt-based approach, which elicits both the independent and joint knowledge about different events for event argument extraction.  ...  To address the above issues, we propose a PrOmpt-based Knowledge Eliciting approach (PoKE), which elicits knowledge from PLMs with two prompt strategies, namely single argument prompt and joint argument  ... 
arXiv:2109.05190v3 fatcat:k4ydkgqvlzal7pabxoaawfsqny

Detecting mismatches among experts' ontologies acquired through knowledge elicitation

Adil Hameed, Derek Sleeman, Alun Preece
2002 Knowledge-Based Systems  
We have constructed a set of ontologies modelled on conceptual structures elicited from several domain experts.  ...  These protocols were analysed from the perspective of both the processes and the domain knowledge to reflect each expert's inherent conceptualisation of the domain.  ...  [12] have identified four distinct dimensions to map knowledge elicitation problems that are likely to occur when several experts are involved during the evolution of a knowledge-based system.  ... 
doi:10.1016/s0950-7051(01)00162-9 fatcat:3thslzpysngh7jtztarggxcof4

Knowledge Elicitation within the Knowledge Base Paradigm: Disentangling Domain Knowledge from Decision Making in Industrial Applications

Marjolein Deryck, Joost Vennekens
2019 International Web Rule Symposium  
In my research I use a combination of rule based and constraint based systems in multiple case studies.  ...  These systems are excellent to define an outcome based on a series of deterministic rules.  ...  IDP and the KBP Knowledge Based Paradigm The IDP engine represents an implementation of the Knowledge Based Paradigm (KBP).  ... 
dblp:conf/ruleml/DeryckV19 fatcat:icmlrrzflberziw26eoqiqft4q

Knowledge Elicitation through Web-Based Data Mining Services [chapter]

Shonali Krishnaswamy, Seng Wai Loke, Arkady Zaslavsky
2001 Lecture Notes in Computer Science  
Knowledge is a vital component for organisational growth and data mining provides the technological basis for automated knowledge elicitation from data sources.  ...  The emergence of Application Service Providers hosting Internet-based data mining services is being seen as a viable alternative for organisations that value their knowledge resources but are constrained  ...  We have presented the structure and contents of XML documents/messages to support knowledge elicitation from web-based data mining services.  ... 
doi:10.1007/3-540-44814-4_12 fatcat:djjc2xoilzfi7hlrk4lfl52b7m

A Human Activity Based Operational Knowledge Elicitation Method

Shuichiro Yamamoto
2016 Procedia Computer Science  
In this paper, a method to elicit and design systems operation knowledge is proposed based on the structural model of human activities.  ...  An example of the proposed method is provided how to elicit and revise the operational knowledge by using an incident management guideline.  ...  System operation knowledge elicitation method Human Activity Model The system operation knowledge elicitation method is a method proposed in which operational activities are recorded based on a) the  ... 
doi:10.1016/j.procs.2016.08.263 fatcat:7mtn2hi7bffntpchhromtdpgpm

A multi-disciplinary review of knowledge acquisition methods: From human to autonomous eliciting agents

George Leu, Hussein Abbass
2016 Knowledge-Based Systems  
acquisition methods, which are based on red-teaming and co-evolution.  ...  In the first two categories, the acquisition of knowledge is seen as a cognitive task analysis exercise, while in the third category knowledge acquisition is treated as an autonomous knowledge-discovery  ...  This is a pre-print of an article published in Knowledge-Based Systems, vol. 105, Elsevier. The final authenticated version is available online at:  ... 
doi:10.1016/j.knosys.2016.02.012 fatcat:4ujojd375zck3kwf2zrzub4q4m

Self-associated concept mapping for representation, elicitation and inference of knowledge

W.M. Wang, C.F. Cheung, W.B. Lee, S.K. Kwok
2008 Knowledge-Based Systems  
With the successful development of the SACM, the capability of Knowledge-based systems (KBS) can be enhanced.  ...  Knowledge elicitation With the advanced development of computer technology and Knowledge-based system (KBS) in the recent decade, organizations are able to record the working activities of each worker  ...  on the step 1 of knowledge elicitation that described in Section 2.2.2.  ... 
doi:10.1016/j.knosys.2006.11.015 fatcat:6stx6xk4tvepvejjsf6nden2au

Extended Rationale Based Model for Tacit Knowledge Elicitation in Requirements Elicitation Context

Halah A. Al-Alshaikh, Abdulrahman A. Mirza, Hessah A. Alsalamah
2020 IEEE Access  
H1: The extended rationale-based (TK-ERB) model will facilitate tacit knowledge elicitation process.  ...  The model called Extended Rationale Based for eliciting Tacit Knowledge (ERBeTK). The goal of the paper is to explore the ability of the model to elicit tacit knowledge.  ... 
doi:10.1109/access.2020.2982837 fatcat:6tfsmq4s3zbidgu3efouy4subm

An FDA-Based Approach for Clustering Elicited Expert Knowledge

Carlos Barrera-Causil, Juan Correa, Andrew Zamecnik, Francisco Torres-Avilés, Fernando Marmolejo-Ramos
2021 Stats  
Expert knowledge elicitation (EKE) aims at obtaining individual representations of experts' beliefs and render them in the form of probability distributions or functions.  ...  In many cases the elicited distributions differ and the challenge in Bayesian inference is then to find ways to reconcile discrepant elicited prior distributions.  ...  Expert knowledge elicitation (EKE) has the goal of producing, via elicitation, a probabilistic distribution that represents the expert's knowledge around a parameter of interest.  ... 
doi:10.3390/stats4010014 fatcat:exsz6vt2rbh4vm67vehz7ryu3e

Elicitation of neurological knowledge with argument-based machine learning

Vida Groznik, Matej Guid, Aleksander Sadikov, Martin Možina, Dejan Georgiev, Veronika Kragelj, Samo Ribarič, Zvezdan Pirtošek, Ivan Bratko
2013 Artificial Intelligence in Medicine  
Objective: The paper describes the use of expert's knowledge in practice and the efficiency of a recently developed technique called argument-based machine learning (ABML) in the knowledge elicitation  ...  Materials and methods: To alleviate the difficult problem of knowledge elicitation from data and domain experts, we used ABML.  ...  Expert system that relies mainly on machine learning techniques for eliciting knowledge is Medical Knowledge Elicitation System (MediKES). In MediKES the expert's knowledge is elicited in two steps.  ... 
doi:10.1016/j.artmed.2012.08.003 pmid:23063772 fatcat:xrsuwyt3ufaqtheitsirbum42e
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