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The Role of Domain Knowledge in Data Mining
, 1995
"... The ideal situation for a Data Mining or Knowledge Discovery system would be for the user to be able to pose a query of the form "Give me something interesting that could be useful" and for the system to discover some useful knowledge for the user. But such a system would be unrealistic as ..."
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The ideal situation for a Data Mining or Knowledge Discovery system would be for the user to be able to pose a query of the form "Give me something interesting that could be useful" and for the system to discover some useful knowledge for the user. But such a system would be unrealistic as databases in the real world are very large and so it would be too inefficient to be workable. So the role of the human within the discovery process is essential. Moreover, the measure of what is meant by "interesting to the user" is dependent on the user as well as the domain within which the Data Mining system is being used. In this paper we discuss the use of domain knowledge within Data Mining. We define three classes of domain knowledge: Hierarchical Generalization Trees (HG-Trees), Attribute Relationship Rules (AR-rules) and EnvironmentBased Constraints (EBC). We discuss how each one of these types of domain knowledge is incorporated into the discovery process within the EDM (Evidential Data Min...
Database Mining in the Architecture of a Semantic Pre-processor for State-Aware Query Optimization
- in Databases". IEE Colloquium on Knowledge Discovery in Databases
, 1994
"... Most applications of in database mining at present seem to be concentrated around the discovery of knowledge for application-oriented decision support. In this paper we describe a tool for enhancing the performance of the database management system itself using semantics captured by database mining ..."
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Most applications of in database mining at present seem to be concentrated around the discovery of knowledge for application-oriented decision support. In this paper we describe a tool for enhancing the performance of the database management system itself using semantics captured by database mining techniques. We investigate the use of database mining in supporting state-aware query optimization where improved performance is sought by dynamically increasing the utilization of available resources. We consider, in particular, the use of semantic knowledge in enhancing the system performance and the utilization of specialized hardware such as ICL's SCAFS by semantic query reformulation. The idea is to discover semantic information about the data stored in the database using database mining techniques and use it to reformulate queries to make better use of available resources at the time of execution of the query. Thus the execution strategy of the query is based on the current state of th...
A Decision Assistant Based on Evidential Reasoning
- Proc. of IEEE ICMLC2006
"... The evidence theory provides an important reasoning mechanism in artificial intelligence, and it has been applied to complex systems to handle uncertainty reasoning. Using a set of easy-to-use interfaces, we have designed an desktop decision assistant system based on the evidence theory. Through the ..."
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The evidence theory provides an important reasoning mechanism in artificial intelligence, and it has been applied to complex systems to handle uncertainty reasoning. Using a set of easy-to-use interfaces, we have designed an desktop decision assistant system based on the evidence theory. Through the easy-to-use interfaces, expert knowledge and opinions or political arguments can be input to the system easily. An incremental evidence combination algorithm is embedded in a reasoning module in the system. Based on the evidential reasoning module, the system can carry out uncertainty reasoning efficiently. Therefore, the system can be applied to enhance human capability to make decisions in daily life, business, or political arguments. As the easy-to-use interfaces are designed, the decision assistant can make decisions in different situations with only a few keyboard clicks. A couple of examples of applications are demonstrated in this paper. Keywords: Decision Assistant; evidential reasoning; decision making; uncertainty reasoning. 1.
Multiknowledge and Computing Network Model for Decision Making and Localisation of Robots
, 2005
"... Contents ..."
Aspects of Uncertainty Handling for Knowledge Discovery in Databases
- University of Ulster
, 1994
"... In this paper we discuss the role of uncertainty in Knowledge Discovery in Databases (KDD) and discuss the applicability of Evidence Theory towards achieving the goal of handling the uncertainty successfully, incorporating it into the discovery process. We claim that Evidence Theory is more su ..."
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In this paper we discuss the role of uncertainty in Knowledge Discovery in Databases (KDD) and discuss the applicability of Evidence Theory towards achieving the goal of handling the uncertainty successfully, incorporating it into the discovery process. We claim that Evidence Theory is more suitable for representing and handling uncertainty within KDD than the Bayesian Model and present a case for the same. We discuss , EDM, our framework for KDD based on Evidence Theory. EDM consists of representation methods for data and knowledge and operators on the data and knowledge that together form the discovery process. Of the different types of operators within EDM, in this paper we limit our discussion to combination operators. We introduce a combination operator called the Proportional Belief Transfer operator and discuss its properties. In particular, we show how it differs from the Dempster-Shafer Orthogonal Sum. 1. Introduction Uncertainty Handling has been an impo...
Database Mining in Spatial Databases
"... The past few years has seen an explosion in the amount of data stored in databases. Apart from textual data, there has been an increase in the amount of pictorial information being stored on computers. Within this data is a lot of implicit, potentially useful information that cannot be extracted man ..."
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The past few years has seen an explosion in the amount of data stored in databases. Apart from textual data, there has been an increase in the amount of pictorial information being stored on computers. Within this data is a lot of implicit, potentially useful information that cannot be extracted manually, simply because of the size of the data and the scarcity of human resources. Thus, the need for automated discovery tools is clear and a lot of effort is being devoted to building such tools. In this paper we present a method for discovery in spatial databases. A general framework for databases mining in relational databases based on evidential theory [ANAN93] is extended to incorporate spatial discovery. We discuss the role of the Dempster-Shafer orthogonal sum combination rule in such a framework. Keywords : Database Mining, Spatial Reasoning, Evidential Theory, Dempster-Shafer Orthogonal Sum. 1. Introduction The discovery of knowledge can come about in many ways. Various modes of d...
Deferred Action: Theoretical model of process architecture design for emergent business processes
"... E-Business modelling and ebusiness systems development assumes fixed company resources, structures, and business processes. Empirical and theoretical evidence suggests that company resources and structures are emergent rather than fixed. Planning business activity in emergent contexts requires flexi ..."
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E-Business modelling and ebusiness systems development assumes fixed company resources, structures, and business processes. Empirical and theoretical evidence suggests that company resources and structures are emergent rather than fixed. Planning business activity in emergent contexts requires flexible ebusiness models based on better management theories and models. This paper builds and proposes a theoretical model of ebusiness systems capable of catering for emergent factors that affect business processes. Drawing on development of theories of the ‘action and design’class the Theory of Deferred Action is invoked as the base theory for the theoretical model. A theoretical model of flexible process architecture is presented by identifying its core components and their relationships, and then illustrated with exemplar flexible process architectures capable of responding to emergent factors. Managerial implications of the model are considered and the model’s generic applicability is discussed.
RESEARCH ESSAY
"... Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioralscience paradigm seeks to develop and verify theories that explain or predict human or organizational behavior. The design-science paradigm seeks to extend the ..."
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Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioralscience paradigm seeks to develop and verify theories that explain or predict human or organizational behavior. The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts. Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology. Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research. In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact. Three recent exemplars in the research literature are used to demonstrate the application MIS Quarterly Vol. 28 No. 1, pp. 75-105/March 2004 75 Hevner et al./Design Science in IS Research of these guidelines. We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community.
Autonomous Robot Control Using Evidential Reasoning
"... Evidence theory has been widely applied to uncertainty reasoning. In this paper a finite state machine with evidential reasoning is proposed to control autonomous robots. The Khepera robot is used to demonstrate the control system. The experimental results show that the control system is able to aut ..."
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Evidence theory has been widely applied to uncertainty reasoning. In this paper a finite state machine with evidential reasoning is proposed to control autonomous robots. The Khepera robot is used to demonstrate the control system. The experimental results show that the control system is able to automatically control the robot behaviours via evidential control rules, which can be designed by humans or automatically extracted using machine learning approaches. Therefore, the control system provides an efficient approach to transfer human knowledge to an autonomous robot.
