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Showing papers in "Knowledge Based Systems in 2000"


Journal ArticleDOI
TL;DR: Social creativity can be supported by new media that allow owners of problems to contribute to framing and solving these problems by creating environments in which stakeholders can act as designers and be more than consumers.
Abstract: Complex design problems require more knowledge than any one single person can possess, and the knowledge relevant to a problem is often distributed and controversial. Rather than being a limiting factor, "symmetry of ignorance" can provide the foundation for social creativity. Bringing different points of view together and trying to create a shared understanding among all stakeholders can lead to new insights, new ideas, and new artifacts. Social creativity can be supported by new media that allow owners of problems to contribute to framing and solving these problems. These new media need to be designed from a meta-design perspective by creating environments in which stakeholders can act as designers and be more than consumers.

206 citations


Journal ArticleDOI
TL;DR: Two experimental studies in a creative professional area: non-routine design and analogical reasoning are conducted to show that the emergence of new ideas takes place in a "constrained cognitive environment", and suggest ways to facilitate creative acts from designers.
Abstract: In order to show that the emergence of new ideas takes place in a "constrained cognitive environment", we conducted two experimental studies in a creative professional area: non-routine design. The first study is focused on the role of analogical reasoning in creativity and, especially, on the nature of potential "sources" of inspiration, which facilitate the evocation process. The second study aims at understanding on which ground designers of different levels of expertise construct their own constrained cognitive environment. Based on the obtained results, we suggest ways to facilitate creative acts from designers.

201 citations


Journal ArticleDOI
TL;DR: KRAFT uses an open and flexible agent architecture in which knowledge sources, knowledge fusing entities and users are all represented by independent KRAFT agents, communicating using a messaging protocol.
Abstract: This paper describes the Knowledge Reuse And Fusion/Transformation (KRAFT) architecture which supports the fusion of knowledge from multiple, distributed, heterogeneous sources. The architecture uses constraints as a common knowledge interchange format, expressed against a common ontology. Knowledge held in local sources can be transformed into a common constraint language, and fused with knowledge from other sources. The fused knowledge is then used to solve some problem or deliver some information to a user. Problem solving in KRAFT typically exploits pre-existing constraint solvers. KRAFT uses an open and flexible agent architecture in which knowledge sources, knowledge fusing entities and users are all represented by independent KRAFT agents, communicating using a messaging protocol. Facilitator agents perform matchmaking and brokerage services between the various kinds of agent. KRAFT is being applied to an example application in the domain of network data services design.

174 citations


Journal ArticleDOI
TL;DR: The development of the PTV (Personalised Television Listings—http://www.ptv.ie) system is described which tackles the information overload associated with modern TV listings data, by providing an Internet-based personalised listings service.
Abstract: The Internet has brought unprecedented access to vast quantities of information. However, in recent times, the problem of information overload has become more and more marked, and we are now reaching a point where it is becoming increasingly difficult to locate the right information at the right time. One avenue of research that is set to improve information access, and relieve the information overload problem, is to develop technologies for automatically personalising information, both in terms of its content and mode of presentation. In this paper we describe the development of the PTV (Personalised Television Listings—http://www.ptv.ie) system which tackles the information overload associated with modern TV listings data, by providing an Internet-based personalised listings service. PTV is capable of automatically compiling personalised guides to match the likes and dislikes of individual users.

161 citations


Journal ArticleDOI
TL;DR: Results indicate that an adaptive solution can provide fraud filtering and case ordering functions for reducing the number of final-line fraud investigations necessary.
Abstract: This paper describes an application of Case-Based Reasoning to the problem of reducing the number of final-line fraud investigations in the credit approval process. The performance of a suite of algorithms, which are applied in combination to determine a diagnosis from a set of retrieved cases, is reported. An adaptive diagnosis algorithm combining several neighbourhood-based and probabilistic algorithms was found to have the best performance, and these results indicate that an adaptive solution can provide fraud filtering and case ordering functions for reducing the number of final-line fraud investigations necessary.

142 citations


Journal ArticleDOI
TL;DR: A model for information filtering on the Web with rough set decision theory is proposed, and it shows that the rough set based model can provide an efficient approach to solve the information overload problem.
Abstract: Machine-learning techniques play the important roles for information filtering. The main objective of machine-learning is to obtain users' profiles. To decrease the burden of on-line learning, it is important to seek suitable structures to represent user information needs. This paper proposes a model for information filtering on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. An experimental system JobAgent is also presented to verify this model, and it shows that the rough set based model can provide an efficient approach to solve the information overload problem.

123 citations


Journal ArticleDOI
John L. Gordon1
TL;DR: Knowledge mapping defined in this work uses learning dependency to organise the map and draws on the ideas of what knowledge is and on spatial representation structures to create a visible knowledge framework that supports the explicit management of knowledge by organisation managers and directors.
Abstract: Knowledge is an interesting concept that has attracted the attention of philosophers for thousands of years. In more recent times, researchers have investigated knowledge in a more applied way with the chief aim of bringing knowledge to life in machines. Artificial Intelligence has provided some degree of rigour to the study of knowledge and Expert Systems are able to use knowledge to solve problems and answer questions. Current business, social, political and technological pressures have forced organisations to take greater control of the knowledge asset. Software suppliers and others offering valuable solutions in this area have unfortunately clouded the issue of knowledge. Information and data control are seen as implicit knowledge management tools and many have abandoned the search for explicit knowledge management methods. Knowledge representation schemes help to identify knowledge. They allow for human understanding and machine application and they can support the automated use of knowledge in problem solving. Some of these representation methods also employ spatial techniques that add an extra dimension to human understanding. Knowledge mapping defined in this work uses learning dependency to organise the map and draws on the ideas of what knowledge is and on spatial representation structures. Knowledge maps can support metrics that provide information about the knowledge asset. Knowledge maps create a visible knowledge framework that supports the explicit management of knowledge by organisation managers and directors. Knowledge maps also offer other advantages to the organisation, the individual and to educational institutions.

122 citations


Journal ArticleDOI
TL;DR: The main issues in using CBR in a CE environment, that is characterised by ill defined and ill structured information during early phases of product development, are textual consistency of terminology, validity of case similarity, and the difficulty in automating case evaluation and adaptation.
Abstract: This paper describes the development and application of case based reasoning (CBR) to provide decision support for project managers and engineers during the early phases of new product development in a concurrent engineering (CE) environment The paper discusses the reasons for using CBR, focussing on issues such as case collection, maintenance, terminology, adaptation, and similarity; and how the final system could contribute towards achieving a CE conducive culture The main issues in using CBR in a CE environment, that is characterised by ill defined and ill structured information during early phases of product development, are textual consistency of terminology, validity of case similarity, and the difficulty in automating case evaluation and adaptation Additionally the paper concludes that using technology like CBR, which can be costly to develop and implement, requires the company to train considerably their managers and team members to document their experiences and knowledge in a manner with which the system can work with and team members can understand There needs to a commitment to maintain and improve the knowledge base—a 'knowledge friendly' culture hence needs to be instilled for CBR tools to succeed

113 citations


Journal ArticleDOI
TL;DR: This work argues that enacted business processes — i.e. workflow management systems — form a solid basis for adequate information support in complex and knowledge-intensive business processes and demonstrates results from two different projects.
Abstract: Explicit modeling of business processes and their enactment in workflow systems have proved to be valuable in increasing the efficiency of work in organizations. We argue that enacted business processes — i.e. workflow management systems — form a solid basis for adequate information support in complex and knowledge-intensive business processes. To support this claim we demonstrate results from two different projects. The VirtualOffice approach employs workflow-context information to support high-precision document analysis and understanding in standard office settings; the combination of workflow context and document analysis allows for the automatic handling of incoming paper mail with respect to the appropriate workflows. The KnowMore approach focuses on the support of people who work on knowledge-intensive tasks by automatic delivery of relevant and goal-specific information. To this end, workflow context, an extended process model, and a detailed modeling of information sources are combined.

108 citations


Journal ArticleDOI
TL;DR: A framework for concept formation is presented that draws on a structure of a design agent that includes sensors, perceptors and conceptors that interact with each other and the external and internal environment of the agent to produce the situation that is a contingent basis for the formation and use of concepts.
Abstract: This paper takes the approach that designing is situated and that concepts are formed as a consequence of the situatedness of designing. The paper presents a framework for concept formation that draws on a structure of a design agent that includes sensors, perceptors and conceptors that interact with each other and the external and internal environment of the agent to produce the situation that is a contingent basis for the formation and use of concepts.

103 citations


Journal ArticleDOI
TL;DR: It is proposed that the perspectives which need to be represented can be characterized as who, what, how, when, where and why knowledge, and necessary levels of abstraction are captured by the Zachman framework for Information Systems Architecture.
Abstract: Full and accurate representation of an organization's knowledge assets, which together constitute “organizational memory”, requires multi-perspective modelling at a number of levels of detail. We propose that the perspectives which need to be represented can be characterized as who, what, how, when, where and why knowledge; these perspectives, and necessary levels of abstraction, are captured by the Zachman framework for Information Systems Architecture. We suggest modelling techniques that might be appropriate for different perspectives and levels of abstraction, and illustrate using examples from a medical domain. We also describe how an individual perspective can become the user interface of a knowledge distribution system, and illustrate this by describing the protocol assistant, a Web-based knowledge-based system capable of representing and reasoning with best practice guidelines (“protocols”) in the medical domain.

Journal ArticleDOI
TL;DR: Details about People-Finder systems implemented at several organizations such as Hewlett–Packard, National Security Agency and Microsoft and future development plans gained through the development of a People-finder KMS are presented.
Abstract: The development of knowledge management systems (KMS) demands that knowledge be obtained, shared and regulated by individuals and knowledge-sharing organizational systems, such as knowledge repositories. People-Finder systems, a type of knowledge repository, attempt to manage knowledge by pointing to experts possessing specific knowledge within an organization. Details about such systems implemented at several organizations such as Hewlett–Packard, National Security Agency and Microsoft are presented. Insights, challenges and future development plans gained through the development of a People-Finder are discussed. Finally, concluding remarks about the role of artificial intelligence in the development of People-Finder KMS and automating the process of profile maintenance are discussed.

Journal ArticleDOI
TL;DR: It is shown that attribute graphs can represent more information and thus can help to retrieve re-usable cases that have similar structures to the new problems in case of educational time-tabling problems.
Abstract: In this paper, we present a case-based reasoning (CBR) approach solving educational time-tabling problems. Following the basic idea behind CBR, the solutions of previously solved problems are employed to aid finding the solutions for new problems. A list of feature–value pairs is insufficient to represent all the necessary information. We show that attribute graphs can represent more information and thus can help to retrieve re-usable cases that have similar structures to the new problems. The case base is organised as a decision tree to store the attribute graphs of solved problems hierarchically. An example is given to illustrate the retrieval, re-use and adaptation of structured cases. The results from our experiments show the effectiveness of the retrieval and adaptation in the proposed method.

Journal ArticleDOI
TL;DR: This method uses a single pass of the database to perform a partial computation of support for all sets encountered in the database, storing this in the form of a set enumeration tree.
Abstract: This paper presents new algorithms for the extraction of association rules from binary databases. Most existing methods operate by generating “candidate” sets, representing combinations of attributes which may be associated, and then testing the database to establish the degree of association. This may involve multiple database passes, and is also likely to encounter problems when dealing with “dense” data due to the increase in the number of sets under consideration. Our methods uses a single pass of the database to perform a partial computation of support for all sets encountered in the database, storing this in the form of a set enumeration tree. We describe algorithms for generating this tree and for using it to generate association rules.

Journal ArticleDOI
TL;DR: Six common strategic elements among US firms that have embraced knowledge management are identified, specifically the need to capitalise on increasingly expensive human resources/process knowledge to achieve competitive advantage in global procurement, in product development, in customer relationship management (CRM) and in value-added services.
Abstract: Knowledge Management has emerged as a predominantly management discipline in the early to mid-90s. The American Productivity and Quality Centre has identified six common strategic elements [1] among US firms that have embraced this new field. Two elements are the formulation of business strategies and the appointment of Chief Knowledge Officers to better focus on the exploitation of core intellectual assets by business and Governments, specifically the need to capitalise on increasingly expensive human resources/process knowledge to achieve competitive advantage in global procurement (supply chain management), in product development, in customer relationship management (CRM) and in value-added services.

Journal ArticleDOI
TL;DR: The reactive scheme is an innovative approach for smart task support that links knowledge from an organizational memory to business tasks and is extended to include proactive inferencing capabilities in order to improve user-friendliness and to facilitate modeling of actual agent support.
Abstract: We describe an approach towards integrating the semantics of semi-structured documents with task-support for (weakly structured) business processes and proactive inferencing capabilities of a desk support agent. The mechanism of our Proactive Inferencing Agent is motivated by the requirements posed in (weakly structured) business processes performed by a typical knowledge worker and by experiences we have made from a first trial with a Reactive Agent Support scheme. Our reactive scheme is an innovative approach for smart task support that links knowledge from an organizational memory to business tasks. The scheme is extended to include proactive inferencing capabilities in order to improve user-friendliness and to facilitate modeling of actual agent support. In particular, the improved scheme copes with varying precision of knowledge found in the organizational memory and it reasons proactively about what might be interesting to you and what might be due in your next step.

Journal ArticleDOI
TL;DR: A rule-based expert system approach for casting process selection is proposed, and an ongoing rule prototype development is described, which recommends the most economical option for a given component.
Abstract: A knowledge-based expert system at the discretion of casting product designers can be employed as a real-time expert advisor to assist product designers to achieve the correct casting design and select the most appropriate casting process for a given component. This paper proposes a rule-based expert system approach for casting process selection, and describes an ongoing rule prototype development. The system in its present development state consists of five interconnected levels each concerning a particular process selection parameter or group of parameters including alloy to be cast, casting geometric features, casting accuracy, production quantity and overall comparative costs. The system progressively evaluates the user's specifications against the capabilities of various casting processes and in each level selects the processes that satisfy the design parameters specified. The final comparative cost level compares the processes that have satisfied all the criteria in the previous levels and recommends the most economical option.

Journal ArticleDOI
TL;DR: The Swiss Life developed the EULE system, which relies on a knowledge representation language which covers data and process aspects as well as the relevant legislation and company regulations.
Abstract: Office tasks related to the processing of contracts in the insurance business are complex and highly dependent on legal and company-specific regulations. Furthermore, due to increasing competition on the market there is a strong pressure to increase the efficiency and quality of office task performance. The only way to meet these manifold requirements is to provide a computer-based guidance and interactive support for office workers. At Swiss Life, we have developed the EULE system that fulfills these requirements. EULE's functionality is in the triangle of Knowledge Representation, Business Process Modeling, and Knowledge Management — the latter because EULE encodes and stores knowledge which is crucial for the company. The system relies on a knowledge representation language which covers data and process aspects as well as the relevant legislation and company regulations.

Journal ArticleDOI
TL;DR: It is identified that systems for supporting collective creativity need to be based on design knowledge that is contextualized; is respectable and trustful; and enables "appropriation" of a design task.
Abstract: The goal of our research is to develop computer systems that support designers' collective creativity; such systems support individual creative aspects in design through the use of representations created by others in the community. We have developed two systems, IAM-eMMa and EVIDII, that both aim at supporting designers in finding visual images that would be useful for their creative design task. IAM-eMMa uses knowledge-based rules, which are constructed by other designers, to retrieve images related to a design task, and infers the underlying "rationale" when a designer chooses one of the images. EVIDII allows designers to associate affective words and images, and then shows several visual representations of the relationships among designers, images and words. By observing designers interacting with the two systems, we have identified that systems for supporting collective creativity need to be based on design knowledge that: (1) is contextualized; (2) is respectable and trustful; and (3) enables "appropriation" of a design task.

Journal ArticleDOI
TL;DR: It is argued that the support of learning of strategic knowledge in collaborative design by computer-mediated means must be based upon empirical evidence about the nature of learning and design practice in the real world.
Abstract: This paper considers aspects of strategic knowledge in design and some implications for designing in collaborative environments. Two key questions underline the concerns. First, how can strategic knowledge for collaborative design be taught and second, what kind of computer-based collaborative designing might best support the learning of strategic knowledge? We argue that the support of learning of strategic knowledge in collaborative design by computer-mediated means must be based upon empirical evidence about the nature of learning and design practice in the real world. This evidence suggests different ways of using computer support for design learning and acquisition of strategic design knowledge. Examples of research by the authors that seeks to provide that evidence are described and an approach to computer system design and evaluation proposed.


Journal ArticleDOI
TL;DR: In this paper, an emotion recognition algorithm based on a neural network and also a method to collect a large speech database containing emotions was proposed to recognize emotions involved in human speech and applied to a computer agent that played a character role in an interactive movie system.
Abstract: In this paper, we first study the recognition of emotions involved in human speech We propose an emotion recognition algorithm based on a neural network and also propose a method to collect a large speech database that contains emotions We carried out emotion recognition experiments based on the neural network trained using this database An emotion recognition rate of approximately 50% was obtained in a speaker-independent mode for eight emotion states We then tried to apply this emotion recognition algorithm to a computer agent that plays a character role in the interactive movie system we are developing We propose to use emotion recognition as key technology for an architecture of the computer characters with both narrative-based and spontaneous interaction capabilities

Journal ArticleDOI
TL;DR: This paper discusses the application of two AI-based techniques, fuzzy logic and artificial neural networks (ANNs), to specific problems related to the operation of oil and gas transport facilities.
Abstract: In recent years, the application of artificial intelligence (AI) based techniques to a wide range of industrial processes has become increasingly common. One reason for this development is the level of maturity of both theory of AI concepts and its implementation into application tools for commercial use. Another very important reason is the persistent drive of many industries to increase efficiencies and the realisation that this requires more effective processing of gained knowledge and information. In the oil and gas industry, due to high saturation levels of many production fields and the complex nature of processes, the need for increased efficiencies and highly effective processing of a large amount of information is particularly evident. Some organisations have recognised the opportunities offered by AI-based techniques and started exploiting them in order to improve knowledge and information handling and process efficiencies. This paper discusses the application of two AI-based techniques, fuzzy logic and artificial neural networks (ANNs), to specific problems related to the operation of oil and gas transport facilities. The background for the work, which is carried out in a co-operation between a university and a leading engineering service provider, is described firstly. This is followed by a brief summary of the fundamentals of the AI techniques considered with respect to their use for industrial purposes. Then, two case studies are presented. The first case study demonstrates the application of fuzzy logic to the control of a pump station in a pipeline system whilst the second case study shows the use of an ANN for the determination of important pipeline characteristics. Problem backgrounds, design procedures and outlines for the implementation of the used AI techniques are given. Finally, benefits of the adopted approaches are highlighted and the wider impact on both industry and research community is discussed.

Journal ArticleDOI
TL;DR: It is argued that two-dimensional positioning of objects in a design support tool serves for the same purpose as sketching does for architectural design.
Abstract: In design, problem analysis is as important as solution synthesis. Strategic knowledge is required not only for constructing a solution but also for framing a problem. While externalized representations play critical roles in design tasks, different types of representations are necessary for different stages of a design task. In early stages of a design task, design support tools need to provide hands-on representations with which a designer can easily perform trial-and-error and examine the whole as well as parts of the whole, allowing the designer to represent any levels of preciseness, as he/she likes. Sketching and drawing with paper and pencil provide an ideal representation for this process. But what about supporting design domains, such as writing or programming, where no sketching exists? In this paper, we argue that two-dimensional positioning of objects in a design support tool serves for the same purpose as sketching does for architectural design. Two-dimensional positioning allows a designer to produce hands-on representations that “talk back” to him/her without forcing the designer to formalize or verbalize what to be externalized. Two systems, ART for writing and RemBoard for component-based programming, illustrate the framework.

Journal ArticleDOI
David McSherry1
TL;DR: An approach to case selection in the construction of a case library is presented in which the most useful case to be added to the library is identified by evaluation of the additional coverage provided by candidate cases.
Abstract: An approach to case selection in the construction of a case library is presented in which the most useful case to be added to the library is identified by evaluation of the additional coverage provided by candidate cases. Cases that can be solved by the addition of a candidate case to the library are discovered in the approach by reversing the direction of case-based reasoning. The computational effort required in the evaluation of candidate cases can be reduced by focusing the search on a specified region of the problem space. The approach has been implemented in CaseMaker, an intelligent case-acquisition tool designed to support the authoring process in a case-based reasoner for estimation tasks.

Journal ArticleDOI
Koichi Hori1
TL;DR: This paper tries to classify different kinds of strategic knowledge, and considers how knowledge-based systems can directly or indirectly exploit the strategic knowledge.
Abstract: This paper considers the diversity of strategic knowledge. It is clear that professionals utilize various kinds of strategic knowledge, but much of it is not well articulated. Some individual habits may be culture determined, and some may be structured knowledge. We try to classify different kinds of strategic knowledge in this paper, and consider how knowledge-based systems can directly or indirectly exploit the strategic knowledge.

Journal ArticleDOI
TL;DR: The paper discusses how advanced document analysis techniques were used to assists intelligence analysts to manage, analyse and assimilate large volumes of electronic documents.
Abstract: This paper examines a software tool that assists Defence intelligence analysts in efficient discovery and assimilation of large volumes of information derived from a range of sources. The Health INTelligence System (HINTS) is a prototype that was developed during a collaborative Research and Development project between Computer Sciences Corporation (CSC) Australia and the Defence Science and Technology Organisation (DSTO). The paper discusses how advanced document analysis techniques were used to assists intelligence analysts to manage, analyse and assimilate large volumes of electronic documents. CSC worked with DSTO to integrate a range of Commercial Off The Shelf (COTS) products and several custom built components. The COTS products included a web search engine, a geo-spatial Graphical User Interface, and an eXtensible Markup Language (XML) server. The project team utilised the above technologies to provide a generic design and interface to ensure the prototype is readily configurable to suit a variety of domains.

Journal ArticleDOI
TL;DR: The architecture of an organisational memory (OM) for road safety analysis is described and how domain knowledge can be exploited and capitalised using case-based reasoning and collaborative work is explained.
Abstract: New generation knowledge-based systems should be fully integrated into their environment, by exploiting existing information sources, and should be flexible and easily extensible. This article describes the architecture of an organisational memory (OM) for road safety analysis. Starting from the design of a knowledge-based system, we show how we address knowledge capitalisation issues through the building of an OM. We present its main components and describe how knowledge engineering techniques can be exploited to build and enrich it. We then describe the major task that exploits the OM as decision support for site analysis. We also explain how domain knowledge can be exploited and capitalised using case-based reasoning and collaborative work.

Journal ArticleDOI
TL;DR: An approach based on a user agent to permit a number of users connected to distant machines to access different information sources in order to satisfy their requests and is endowed with the ability to filter and refine the search, thus improving its service to the users.
Abstract: This paper presents an approach based on a user agent to permit a number of users connected to distant machines to access different information sources in order to satisfy their requests. This user agent permits the simplification of the information search from distributed sources by making them transparent to the users. The agent considers the specific needs of each user during the search and responds with reference to their profile. It also permits the processing of one or more information requests by one or more users, as well as concurrent responses to each of them. Moreover, the agent provides its users with a measure of interaction, in order to enhance the quality and quantity of the results obtained. As a result, the agent is endowed with the ability to filter and refine the search, thus improving its service to the users.

Journal ArticleDOI
TL;DR: Results on real data sets show that RFP achieves better or comparable accuracy and is faster than both KNN and Rule-based regression algorithms.
Abstract: This paper describes a machine learning method, called Regression on Feature Projections (RFP), for predicting a real-valued target feature, given the values of multiple predictive features. In RFP training is based on simply storing the projections of the training instances on each feature separately. Prediction of the target value for a query point is obtained through two averaging procedures executed sequentially. The first averaging process is to find the individual predictions of features by using the K-Nearest Neighbor (KNN) algorithm. The second averaging process combines the predictions of all features. During the first averaging step, each feature is associated with a weight in order to determine the prediction ability of the feature at the local query point. The weights, found for each local query point, are used in the second prediction step and enforce the method to have an adaptive or context-sensitive nature. We have compared RFP with KNN and the rule based-regression algorithms. Results on real data sets show that RFP achieves better or comparable accuracy and is faster than both KNN and Rule-based regression algorithms.