INTEGRATION OF INFORMATION SYSTEMS TECHNOLOGIES TO SUPPORT CONSULTATION IN AN INFORMATION CENTER

This paper presents an approach for integrating different types of information systems technologies to support the functions of an Information Center (IC). A knowledge based system, Information Center Expert/Help Service (ICE/H), has been developed to provide support for the help services of an IC. A general process model to represent the consultation process in an IC is described. Based on this model, an architecture to support the consultation process has been developed. The architecture depicts the use of a knowledge management system, a data management system and a communication (E-mail) system to emulate the consultation process. The ICE/H system has been implemented using this architecture to support an IC with 5000 users

Visualized Architecture Knowledge Management Collaboration Services

Software (system) architecture knowledge is a critical element in making effective design/ implementation decisions for Information Technology departments within companies. This knowledge can be codified and/ or personalized so as to harness the advantages and avoid the missed steps of implementers before us. In research of architecture knowledge enablement, there have been a few ventures, including but not limited to, Processcentric Architecture Knowledge Management Environment (PAKME) [3] and Architecture Design Decision Support System (ADDSS) [4]. In study of these ventures, we find modest attempts at focusing on dissecting types of architecture knowledge and enabling access to details through web tools. The purpose of this paper is to document the design and features of a web tool, namely Visualized Architecture Knowledge Management Collaboration Services (VAKMCS) and its approach in providing an innovative way at accessing and interacting with architecture information to make sound investment decision on IT projects

Knowledge-based design support and inductive learning

Designing and learning are closely related activities in that design as an ill-structure problem involves identifying the problem of the design as well as finding its solutions. A knowledge-based design support system should support learning by capturing and reusing design knowledge. This thesis addresses two fundamental problems in computational support to design activities: the development of an intelligent design support system architecture and the integration of inductive learning techniques in this architecture.This research is motivated by the belief that (1) the early stage of the design process can be modelled as an incremental learning process in which the structure of a design problem or the product data model of an artefact is developed using inductive learning techniques, and (2) the capability of a knowledge-based design support system can be enhanced by accumulating and storing reusable design product and process information.In order to incorporate inductive learning techniques into a knowledge-based design model and an integrated knowledge-based design support system architecture, the computational techniques for developing a knowledge-based design support system architecture and the role of inductive learning in Al-based design are investigated. This investigation gives a background to the development of an incremental learning model for design suitable for a class of design tasks whose structures are not well known initially.This incremental learning model for design is used as a basis to develop a knowledge-based design support system architecture that can be used as a kernel for knowledge-based design applications. This architecture integrates a number of computational techniques to support the representation and reasoning of design knowledge. In particular, it integrates a blackboard control system with an assumption-based truth maintenance system in an object-oriented environment to support the exploration of multiple design solutions by supporting the exploration and management of design contexts.As an integral part of this knowledge-based design support architecture, a design concept learning system utilising a number of unsupervised inductive learning techniques is developed. This design concept learning system combines concept formation techniques with design heuristics as background knowledge to build a design concept tree from raw data or past design examples. The design concept tree is used as a conceptual structure for the exploration of new designs.The effectiveness of this knowledge-based design support architecture and the design concept learning system is demonstrated through a realistic design domain, the design of small-molecule drugs one of the key tasks of which is to identify a pharmacophore description (the structure of a design problem) from known molecule examples.In this thesis, knowledge-based design and inductive learning techniques are first reviewed. Based on this review, an incremental learning model and an integrated architecture for intelligent design support are presented. The implementation of this architecture and a design concept learning system is then described. The application of the architecture and the design concept learning system in the domain of small-molecule drug design is then discussed. The evaluation of the architecture and the design concept learning system within and beyond this particular domain, and future research directions are finally discussed

An Intelligent Knowledge Management System from a Semantic Perspective

Abstract. Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

An Intelligent Knowledge Management System from a Semantic Perspective

Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

Supporting the emergence of knowledge communities in industrial association groups in the construction sector

association group in the construction sector. This system is a result of the Know-Construct project which aimed at providing association sponsored SME communities of the construction sector with a sophisticated information management platform and community building tools for knowledge sharing and customer support. The paper begins by characterizing the so-called construction industry knowledge community (CIK). The generic architecture of the supporting system (Knowledge Community Support - KCS and Customer Needs Management - CNM) is described, in terms of information and knowledge management, community building facilities and semantic resources management. The Know-Construct project decided to re-use, as far as possible, existing ontologies, classification systems and other semantic resources to develop a system for the integration, management and reuse of the area specific knowledge. Part of the paper describes the approach followed, as well the lessons learned. The final part of the paper depicts the approach to the actual introduction of the system in the community.info:eu-repo/semantics/publishedVersio

A Task-based Support Architecture for Developing Point-of-care Clinical Decision Support Systems for the Emergency Department

Objectives: The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. Methods: The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. Results: The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE – a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. Conclusions: The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs

Improving knowledge management in construction industry by combining ontology with collaborative technologies

University of Technology, Sydney. Faculty of Design, Architecture and Building.The concept of knowledge management has been introduced to the construction industry for many years. Recently, its importance is more recognized as modern construction projects are more complex and globalized. Managing knowledge assets is a challenge, especially in the construction industry, as it is characterized as a project-based business which delivers one-of-a-kind product, and it has a highly fragmented working environment. While explicit knowledge has been handled by many existing commercial project information management systems, tacit knowledge is more difficult to handle because of its intangible nature, and so far very few computer systems have attempted to handle tacit knowledge. Tacit knowledge is usually created and transferred in a social environment, and maintained mainly in human's head. Therefore a combination of a group of advanced IT technologies should be adopted for efficient knowledge manipulating. In this research, web-based collaborative system, blogging technology, domain ontology and semantic web environment are used together to provide technology support for knowledge management. The original contribution of this research is that it demonstrates the effectiveness of using construction domain ontology in semantic blogging to promote knowledge sharing. While focusing on technology support, this research also investigates appropriate KM framework and system architecture for small and medium sized construction organizations. A prototype knowledge management system is proposed and implemented; some knowledge management cases are presented to demonstrate how the proposed KM framework and advanced IT tools could help the KM process in the construction industry

From a Configuration Management to a Cognitive Radio Management of SDR Systems

International audienceThis paper proposes a functional management architecture for Cognitive Radio systems. It relies on a previously defined configuration management architecture for multi-standard SDR systems, and complement it to support cognitive radio features. This paper explains the requirements of Cognitive Radio systems in terms of reconfiguration, smartness and sensing capabilities. A configuration management architecture capable of dealing with the hardware heterogeneity and a wide range of reconfiguration scenarios expected with SDR systems is presented. The management is distributed over the system and a hierarchical dependency is set on 3 layers, each having a different level of knowledge of the system and the associated hardware constraints of the elements it supervises. Then a cognitive management functional architecture is derived from the previous one, copying the 3 layers of hierarchy. The roles of the elements of each layer are discussed, as well as their respective interactions and their relationships with the elements of the configuration management architecture

A Knowledge-Engine Architecture for a Competence Management Information System

This paper describes the ongoing project to develop a knowledge-engine architecture that is being specified and developed by a Portuguese software development company called Shortcut. The primary goal of this work is create an architecture suitable for use, initially, in a Competence Management System (CMS) but also scalable for later use in more generic forms of Knowledge Management Systems (KMS). In general, Knowledge Management (KM) initiatives promote the management, i.e. the creation, storage and sharing, of knowledge assets within an organization. The practical focus of our work is to support the management of employees’ competencies through using a KM approach to create a web based CMS based on a structured content management infrastructure. The system is designed using an ontology-driven framework that incorporates expert annotations which integrate aspects of less tangible knowledge, such as contextual information with more structured knowledge such as that stored in databases, procedures, manuals, books and reports. The theoretical focus of the work is on the representation of competence-based knowledge resources, such as human capital, skills, heuristics acquired during project development, best practices and lessons-learned. This work should contribute for improving the understanding and analysis of the collective knowledge, skills and competencies that are created through problem solving in day-to-day activities and could act as a meeting point for issues around problem solving in complex organizations and context-based information retrieval