The Experts below are selected from a list of 478650 Experts worldwide ranked by ideXlab platform
Gregory F Ashby - One of the best experts on this subject based on the ideXlab platform.
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Information Integration category learning and the human uncertainty response
Memory & Cognition, 2011Co-Authors: Erick J Paul, Joseph Boomer, David J Smith, Gregory F AshbyAbstract:The human response to uncertainty has been well studied in tasks requiring attention and declarative memory systems. However, uncertainty monitoring and control have not been studied in multi-dimensional, Information-Integration categorization tasks that rely on non-declarative procedural memory. Three experiments are described that investigated the human uncertainty response in such tasks. Experiment 1 showed that following standard categorization training, uncertainty responding was similar in Information-Integration tasks and rule-based tasks requiring declarative memory. In Experiment 2, however, uncertainty responding in untrained Information-Integration tasks impaired the ability of many participants to master those tasks. Finally, Experiment 3 showed that the deficit observed in Experiment 2 was not because of the uncertainty response option per se, but rather because the uncertainty response provided participants a mechanism via which to eliminate stimuli that were inconsistent with a simple declarative response strategy. These results are considered in the light of recent models of category learning and metacognition.
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response processes in Information Integration category learning
Neurobiology of Learning and Memory, 2008Co-Authors: Brian J Spiering, Gregory F AshbyAbstract:Much recent evidence suggests that human category learning is mediated by multiple systems. Evidence suggests that at least one of these depends on procedural learning within the basal ganglia. Information-Integration categorization tasks are thought to load heavily on this procedural-learning system. The results of several previous studies were interpreted to suggest that response positions are learned in Information-Integration tasks. This hypothesis was tested in two experiments. Experiment 1 showed that Information-Integration category learning was slowed but not disrupted when the spatial location of the responses varied randomly across trials. Experiment 2 showed that Information-Integration learning was impaired if category membership was signaled by responding to a Yes/No question and the category label had no consistent spatial location. These results suggest that Information-Integration category learning does not require consistent response locations. In these experiments, a consistent association between a category and a response feature was sufficient. The implication of these results for the neurobiology of Information-Integration category learning is discussed.
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observational versus feedback training in rule based and Information Integration category learning
Memory & Cognition, 2002Co-Authors: Gregory F Ashby, Todd W Maddox, Corey J BohilAbstract:The effects of two different kinds of categorization training were investigated. In observational training, observers are presented with a category label and then shown an exemplar from that category. In feedback training, they are shown an exemplar, asked to assign it to a category, and then given feedback about the accuracy of their response. These two types of training were compared as observers learned two types of category structures—those in which optimal accuracy could be achieved via some explicit rule-based strategy, and those in which optimal accuracy required integrating Information from separate perceptual dimensions at some predecisional stage. There was an overall advantage for feedback training over observational training, but most importantly, type of training interacted strongly with type of category structure. With rule-based structures, the effects of training type were small, but with Information-Integration structures, accuracy was substantially higher with feedback training, and people were less likely to use suboptimal rule-based strategies. The implications of these results for current theories of category learning are discussed.
I L Kong - One of the best experts on this subject based on the ideXlab platform.
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a schema and ontology aided intelligent Information Integration
Expert Systems With Applications, 2009Co-Authors: Jialang Seng, I L KongAbstract:The research issues of intelligent Information Integration have become ubiquitous and critically important in e-business (EB) with the increasing dependence on Internet/Intranet and Information technology (IT). Accessing the intelligent Information sources separately without Integration may lead to the chaos of Information requested. It is also not cost-effective in EB settings. A common general way to deal with heterogeneity problems in traditional III is to create a common data model. The eXtensible Markup Language (XML) has been the standard data document format for exchanging Information on the Web. XML only deals with the structural heterogeneity; it can barely handle the semantic heterogeneity. Ontologies are regarded as an important and natural means to represent the implicit semantics and relationships in the real world. And they are used to assist to reach semantic interoperability in III in this research. In this paper, we provide a generic construct orientation no ad hoc method to generate the global schema to enable the web-based alternative to traditional III. We provide a wiser query method over multiple intelligent Information sources by applying global-as-view (GAV) and local-as-view (LAV) approach with the use of ontology to enhance both structural and semantic interoperability of the underlying intelligent Information sources. We construct a prototype implementing the method to provide a proof on the validity and feasibility.
Edward W N Bernroider - One of the best experts on this subject based on the ideXlab platform.
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The performance of contingencies of supply chain Information Integration: The roles of product and market complexity
International Journal of Production Economics, 2015Co-Authors: Christina W Y Wong, Kee-hung Lai, Edward W N BernroiderAbstract:Abstract Although Information Integration is generally considered beneficial for supply chain management, the performance of supply chain Information Integration is found with mixed results in both practices and the extant literature. Based on the organizational Information processing theory, this study aims to show how the contextual factors pertaining to product and market complexity moderate the relationship of supply chain Information Integration with financial and operational performance outcomes. Using survey data collected from 188 wholesale trading firms, we found that the extent to which supply chain Information Integration has a positive impact on business performance is contingent on the level of product and market complexity. Specifically, supply chain Information Integration facilitates greater performance improvements when it serves less complex products or is operated under a highly complex market environment. The study findings provide insights to managers and advance theoretical development by providing empirical evidence that supply chain Information Integration is helpful for mitigating uncertainties in supply chain management and the performance contingencies of such Integration on the two contextual factors.
Honglin Li - One of the best experts on this subject based on the ideXlab platform.
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Ontology-based Information Integration in virtual learning environment
The 2005 IEEE WIC ACM International Conference on Web Intelligence (WI'05), 2005Co-Authors: Aijuan Dong, Honglin LiAbstract:A good virtual learning environment should deliver relevant learning materials to learners at the most appropriate time and locations to facilitate learners' acquisition of knowledge and skills. In this paper, we propose ontology-based Information Integration in virtual learning environment using ontology and Web services. Relevant concepts extracted from domain ontology provide ontology-based browsing space that allows users to browse and select relevant terms of interest and increases the degree of relevancy. By using Web services to integrate learning materials from heterogeneous public domain data sources, applications do not need to know the internal structure and working of public domain data sources, and reuse existing applications and recourses. We use gene ontology, PubMed eUtils and Google Web APIs to demonstrate our idea. The implementation involves techniques in image and video processing, database management, programming, and multimedia learning materials presentation.
Yohan Choi - One of the best experts on this subject based on the ideXlab platform.
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agent based layered intelligent Information Integration system using ontology and metadata registry
Lecture Notes in Computer Science, 2003Co-Authors: Jeongoog Lee, Yohan ChoiAbstract:To share and exchange Information, especially in the multi-database environments, each component database must know the meanings and the representations of the Information of other sources. And users who are searching integrated Information on the Web have limitation to obtain schema Information for the underlying component databases. To solve these problems, in this paper, we present an Agent-based Layered Intelligent Information Integration System (ALI3S) using metadata registry(MDR) and ontology. 1 The purpose of the proposed architecture is to define an Information Integration model, which combines characteristics of both standard specification of MDRs and functionality of ontology for the concepts and relations. Adopting agent technology to the proposed model plays a key role to support the hierarchical and independent Information Integration architecture.
