MODEL OF GENERALIZED REPRESENTATION OF TEMPORAL KNOWLEDGE FOR TASKS OF SUPPORT OF ADMINISTRATIVE DECISIONS
DOI:
https://doi.org/10.20998/2079-0023.2020.01.03Keywords:
t, emporal knowledge base, temporal rules, logical facts, the sequence of states of the control objectAbstract
The subject of the research is the processes of building and using temporal knowledge, which determine the order of implementation of managerial decisions within the framework of organizational management. The goal is to develop a temporal knowledge representation model to determine the sequence of control actions over time as part of a management decision, taking into account the level of the organizational hierarchy at which these actions are implemented. To achieve this goal, the problems of structuring the factors determining the differences in the presentation and use of temporal knowledge, as well as the development of a generalized model of temporal knowledge to support managerial decisions, are solved. It is shown that the key differences between temporal and causal dependencies are associated with the use of a combination of formal and informal knowledge of performers about causal relationships between control actions as part of a management decision to build a sequence of actions in time, as well as the probabilistic properties of temporal relationships. A generalized model of temporal knowledge is proposed, designed to support managerial decisions. The model includes many generalized facts, as well as a set of temporal and hierarchical relationships between these facts. Facts reflect known states of the control object. Each generalized fact is formed on the basis of a conjunction of elementary facts. An elementary fact sets the value of a certain property of a control object. Temporal relationships determine the sequence of facts over time. The organizational hierarchy level for facts is set using logical operations. In practical terms, the proposed model is focused on building a temporal knowledge base. Conclusion based on such a knowledge base makes it possible to determine the probable sequence of control actions that lead to a sequence of transitions between states, which allows achieving the target state of the control object. This makes it possible to form a set of possible alternative options for implementing a managerial decision in the event of abnormal conditions of the control object.References
Frank Harrison E.., Monique A. The essence of management decision. Management Decision. 2000, vol. 38, issue 7, рр. 462–470.
Smirnov E. А. Upravlencheskie resheniya [Management decisions] Мoscow: Ifra-M Publ., 2001. 264 p.
Chala O. Method for detecting anomalous states of a control object in information systems based on the analysis of temporal data and knowledge. EUREKA: Physics and Engineering. 2018, vol. 6, рр. 28– 35.
Levykin V. М, Chala О. V. Pidtrimka prijnyattya rishen v informacino-upravlyayuchih sistemah z vikoristannyam temporalnoyi bazi znan [Decision support in information and management systems using a temporal knowledge base]. Suchasni informacijni sistemi [Modern information systems], 2018, vol. 2, no. 4, рр. 101–107.
Levykin V., Chala O. Metod pidtrimki upravlinskih rishen v umovah neviznachenosti na osnovi temporalnih znan [Method of support of managerial decisions in conditions of uncertainty on the basis of temporal knowledge]. Bionika intelektu [Bionics of Intelligence]. 2018, no 2 (91), pp. 54–59.
Kalynychenko O., Chaly S., Bodyanskiy Y., Golian V., Golian N. Implementation of Search Mechanism for Implicit Dependences in Process Mining. Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2013 IEEE 7th International Conference. Vol. 1, pp. 138–14.
Chalyi S., Leshchynskyi V., Leshchynska I. Method of forming recommendations using temporal constraints in a situation of cyclic cold start of the recommender system. EUREKA: Physics and Engineering. Vol. 4, pp. 34–40.
Domingos P. Lowd D., Kok S., Poon H., Richardson M., Singla P. Just Add Weights: Markov Logic for the Semantic Web. International Workshop on Uncertainty Reasoning for the Semantic Web. 2006, pp. 1–25.
Domingos P. Learning, logic, and probability: A unified view. Proceedings of the IBERAMIA 2006, SBIA 2006: Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. Brazil, 2006. URL: springer.com/chapter/10.1007/11874850_2 (accessed: 18.05.2020).
Chalyi S. F., Leshchynskyi V. O., Leshchynska I. O. Modelyuvannya poyasnen shodo rekomendovanogo pereliku ob’yektiv z urahuvannyam temporalnogo aspektu viboru koristuvacha [Modeling explanations for the recommended list of items based on the temporal dimension of user choice]. Sistemi upravlinnya, navigaciyi ta zv’yazku [Control, Navigation and Communication Systems]. 2019, vol. 6, no. 58. pp. 97–101.
Chalyi S. F., Leshchynskyi V. O., Leshchynska I. O. Доповнення вхідних даних рекомендаційної системи в ситуації циклічного холодного старту з використанням темпоральних обмежень типу «NEXT». [Supplementing the input of the recommendation system in a cyclic cold start situation using temporal constraints of the “next” type].Sistemi upravlinnya, navigaciyi ta zv’yazku [Control, Navigation and Communication Systems]. 2019, vol. 4(56), pp. 105– 109.
Levykin V., Chala O. Development of a method of probabilistic inference of sequences of business process activities to support business process management. Eastern-European Journal of Eenterprise Technologies. 2018, no. 5/3(95), pp. 16–24.
Levykin V., Chala O. Development of information technology to support management decisions using the probabilistic inference in a temporal knowledge base. Problems of information technologies. 2018, no. 24, pp. 35–44.
Downloads
How to Cite
Issue
Section
License
Copyright (c) 2020 Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information TechnologiesAuthors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
