Michael Pashkin

Constraint-driven Methodology for Context-based Decision Support

An approach to intelligent decision making support at its tactical and operational levels is discussed. The main idea behind the approach consists in knowledge-based creation of a problem model, instantiation of the problem by data values from information sources, and its interpretation as a constraint satisfaction problem. The proposed approach stages are mapped into Simon’s decision process model. Approach applicability is illustrated through a case study of disaster response.

Context-aware operational decision support

The paper presents research on context-aware operational decision support for emergency management. Ontology-based context model is proposed for organization of context-aware decision support Two types of context are used: abstract context that is an ontology-based model integrating information and knowledge relevant to a decision situation, and operational context that is an instantiated abstract context within the personalization of decision support systems multi-role decision support is offered proposed ideas are illustrated through a case study of disaster relief and evacuation.

Context-Based Disaster Management Support

The paper describes an approach to decision making support for disaster management. The approach is based on the methodology that assumes three levels of information integration. The application domain is described via an application ontology using the formalism of object-oriented constraint networks. The problem is described via an abstract context that is obtained as a result of the slicing operation on the application ontology. Finally, filling the abstract context with up-to-date information about the current situation produces an operational context. Contexts of both types share the same knowledge representation formalism that is used by the application ontology. As a result the operational context can be considered as a constraint satisfaction problem. Solving this task produces feasible decisions in the current situation

Moving towards automatic generation of information demand contexts: an approach based on enterprise models and ontology slicing

This paper outlines the first experiences of an approach for automatically deriving information demands in order to provide users with demand-driven information supply and decision support The presented approach is based on the idea that information demands with respect to work activities can be identified by examining the contexts in which they exist and that a suitable source for such contexts are Enterprise Models However, deriving contexts manually from large and complex models is very time consuming and it is therefore proposed that a better approach is to, based on an Enterprise Model, produce a domain ontology and from this then automatically derive the information demand contexts that exist in the model.

Intelligent Support for Distributed Operational Decision Making

An integrated technology for intelligent support for distributed operational decision making is proposed. The conceptual framework implementing the technology consists of building an ontology-based model of the problem to be solved by the decision maker, formalization of the problem with a set of constraints, instantiation with the data values provided by environmental information sources, and interpretation it as constraint satisfaction problem. The problem is modelled by two types of contexts: abstract and operational. The integrated technology embodies advanced technologies for ontology & context management, and constraint satisfaction

Multi-Agent Decision Support System for Disaster Response and Evacuation

The paper describes an agent-based approach and its application to intelligent support of disaster response and evacuation operations. The approach is based on the idea of knowledge logistics which stands for integration and transfer of the right knowledge from distributed sources to the right person within the right context at the right time to the right purpose. The problem in the approach is represented as configuring a network of knowledge sources and approach is called “KSNet-approach”. The paper concentrates on such aspects as multiagent architecture, knowledge representation formalism and presents an application of the approach via a case study.

Web-Service based Distributed System for Decision Support in Emergency Situations

Availability of relevant up-to-date information is of high importance for situation management in disaster events. The paper proposes methodology and prototype architecture for operational decision support based on information acquisition from heterogeneous sources. General scenario of the decision support system operation is described in detail. Usage of Web-services allows integration of distributed system components using existing Internet resources and facilities. Some advantages of such facilities (e.g., using a mobile phone for receiving assignments) are presented.

User-Centric Information Management for Decision Support in Disaster Relief & Evacuation

Operations oriented to disaster relief & evacuation management usually takes place in a continuously changing environment, what requires application of situation management principles. Context is information that can be used to characterize a situation or an entity where the entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and the application themselves. Thereby application of context management technology to disaster relief & evacuation can significantly improve the decision making processes in this area. However, decision making cannot be efficient without user-centric information management. In the presented work the profiling techniques are used for this purpose. Developed user profile model and its application are presented. The model consists of the user context (information used to facilitate the decision support process) and history of the activities. The history is used to reveal tacit user preferences that are included into the user context

Personalized configuration of immaterial products

Product configuration deals with design of a new product from existing components. Recently, research on product configuration has shifted to the stage of conceptual modelling. Conceptual product models do not depend on the modelling purpose and therefore can be tailored to the current customer needs. The paper proposes an ontology-based scenario for configuration of immaterial products. The scenario suggests three product configuration operations: removal, supplement, and change. Product customization is supported by involvement of the customer in the process of configuration and by using information from the customer profile. The scenario execution is demonstrated by a particular case of configuration of a mobile operator product in the form of supplement this product with a service. An ontology for mobile product operator is proposed. OWL and SPARQL are used for ontology specification and querying.

OOTW Intelligent Support: Fusion-Based Knowledge Logistics for Health Service Application

*OOTW include missions where sides are required to intensively cooperate. As a result an efficient knowledge sharing between multiple participating parties is required to provide for situation awareness and consequently to successfully manage any OOTW operation. Thereby it is necessary that the right knowledge from distributed sources is integrated and transferred to the right person within the right context at the right time to the right purpose. The aggregate of these interrelated activities is referred to as knowledge logistics (KL). The paper presents an approach that implements KL for an intelligent support of OOTW. Within the approach KL is coupled with information fusion based on constraint satisfaction methodology. Health service logistics is here considered as one of the approach applications what is illustrated via a case study of on-the-fly portable hospital configuration.