An Intelligent Help-Desk Framework for Effective Troubleshooting

Nowadays, technological infrastructure requires an intelligent virtual environment based on decision processes. These processes allow the coordination of individual elements and the tasks that connect them. Thus, incident resolution must be efficient and effective to achieve maximum productivity. In this paper, we present the design and implementation of an intelligent decision-support system applied in technology infrastructure at the University of Seville (Spain). We have used a Case Based Reasoning (CBR) methodology and an ontology to develop an intelligent system for supporting expert diagnosis and intelligent management of incidents. This is an innovative and interdisciplinary approach to knowledge management in problem-solving processes that are related to environmental issues. Our system provides an automatic semantic indexing for the generating of question/answer pairs, a case based reasoning technique for finding similar questions, and an integration of external information sources via ontologies. A real ontology-based question/answer platform named ExpertSOS is presented as a proof of concept. The intelligent diagnosis platform is able to identify and isolate the most likely cause of infrastructure failure in case of a faulty operation

B mu G@Sbase - a microarray database and analysis tool

The manufacture and use of a whole-genome microarray is a complex process and it is essential that all data surrounding the process is stored, is accessible and can be easily associated with the data generated following hybridization and scanning. As part of a program funded by the Wellcome Trust, the Bacterial Microarray Group at St. George's Hospital Medical School (BμG@S) will generate whole-genome microarrays for 12 bacterial pathogens for use in collaboration with specialist research groups. BμG@S will collaborate with these groups at all levels, including the experimental design, methodology and analysis. In addition, we will provide informatic support in the form of a database system (BμG@Sbase). BμG@Sbase will provide access through a web interface to the microarray design data and will allow individual users to store their data in a searchable, secure manner. Tools developed by BμG@S in collaboration with specific research groups investigating analysis methodology will also be made available to those groups using the arrays and submitting data to BμG@Sbase

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Measuring Performance in Knowledge Intensive Processes

Knowledge-Intensive Processes (KIPs) are processes whose execution is heavily dependent on knowledge workers performing various interconnected knowledge-intensive decision-making tasks. Among other characteristics, KIPs are usually non-repeatable, collaboration-oriented, unpredictable and, in many cases, driven by implicit knowledge, derived from the capabilities and previous experiences of participants. Despite the growing body of research focused on understanding KIPs and on proposing systems to support these KIPs, the research question on how to define performance measures thereon remains open. In this paper, we address this issue with a proposal to enable the performance management of KIPs. Our approach comprises an ontology that allows us to define process performance indicators (PPIs) in the context of KIPs, and a methodology that builds on the ontology and the concepts of lead and lag indicators to provide process participants with actionable guidelines that help them conduct the KIP in a way that fulfills a set of performance goals. Both the ontology and the methodology have been applied to a case study of a real organization in Brazil to manage the performance of an Incident Troubleshooting Process within an ICT (Information and Communications Technology) Outsourcing Company.European Union's Horizon 2020 No 645751 (RISE_BPM)Junta de Andalucía P12-TIC-1867 (COPAS)Ministerio de Economía y Competitividad TIN2015-70560-R (BELI

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Capitalization and sharing of lessons learned play an essential role in managing the activities of industrial systems. This is particularly the case for the maintenance management, especially for distributed systems often associated with collaborative decision-making systems. Our contribution focuses on the formalization of the expert knowledge required for maintenance actors that will easily engage support tools to accomplish their missions in collaborative frameworks. To do this, we use the conceptual graphs formalism with their reasoning operations for the comparison and integration of several conceptual graph rules corresponding to different viewpoint of experts. The proposed approach is applied to a case study focusing on the maintenance management of a rotary machinery system

Visual Execution Analysis for Multiagent Systems

Multiagent systems have become increasingly important in developing complex software systems. Multiagent systems introduce collective intelligence and provide benefits such as flexibility, scalability, decentralization, and increased reliability. A software agent is a high-level software abstraction that is capable of performing given tasks in an environment without human intervention. Although multiagent systems provide a convenient and powerful way to organize complex software systems, developing such system is very complicated. To help manage this complexity this research develops a methodology and technique for analyzing, monitoring and troubleshooting multiagent systems execution. This is accomplished by visualizing a multiagent system at multiple levels of abstraction to capture the relationships and dependencies among the agents

Towards a system redesign for better performance and customer satisfaction : a case study of the ICTS helpdesk at the University of Cape Town

Includes bibliographical references.This paper presents the findings from a study, which was carried out to investigate how the design of knowledge management systems could be improved for enhanced performance and greater customer satisfaction. The ICTS Department's helpdesk at the University of Cape Town, South Africa, was the venue for this case study. The study set out to meet the following objectives: - undertaking a knowledge acquisition strategy by carrying out a systems evaluation and analysis of the existing web-based user support system, - suggesting a knowledge representation model for an adaptive web-based user support system, and - developing and testing an online troubleshooter prototype for an improved knowledge use support system. To achieve the objectives of the study, knowledge engineering techniques were deployed on top of a qualitative research design. Questionnaires, which were supplemented by interview guides and observations, were the research tools used in gathering the data. In addition to this, a representative sample of the ICTS clientele and management was interviewed. It was discovered that poorly designed knowledge management systems cause frustration among the clientele who interact with the system. Specifically, it was found that the language used for knowledge representation plays a vital role in determining how best users can interpret knowledge items in a given knowledge domain. In other words, knowledge modelling and representation can improve knowledge representation if knowledge engineering techniques are appropriately followed in designing knowledge based systems. It was concluded that knowledge representation can be improved significantly if, firstly, the ontology technique is embraced as a mechanism of knowledge representation. Secondly, using hierarchies and taxonomies improves navigability in the knowledge structure. Thirdly, visual knowledge representation that supplements textual knowledge adds more meaning to the user, and is such a major and important technique that it can even cater for novice users

Adaptive hypermedia for education and training

Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, Kühme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b)