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作者：Chung, W; Chen, H; Nunamaker, JF Jr
作者单位：University of Texas System; University of Texas El Paso; University of Arizona; University of Arizona
摘要：Information overload often hinders knowledge discovery on the Web. Existing tools lack analysis and visualization capabilities. Search engine displays often overwhelm users with irrelevant information. This research proposes a visual framework for knowledge discovery on the Web. The framework incorporates Web mining, clustering, and visualization techniques to support effective exploration of knowledge. Two new browsing methods were developed and applied to the business intelligence domain: We...
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作者：Bendahan, S; Camponovo, G; Monzani, JS; Pigneur, Y
作者单位：University of Lausanne; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：In large-scale negotiation problems and in assessments of complex and uncertain environments, it is vital to analyze the different stakeholders involved and to evaluate their positions in the negotiations. This paper extends a model, which merges previous multi-issue and actor-focused methods, based on power relationships between stakeholders and their ability to bargain in order to increase their utility. The model has already used for assessing a public WLAN landscape. The paper emphasizes t...
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作者：Fan, WG; Gordon, MD; Pathak, P
作者单位：Virginia Polytechnic Institute & State University; University of Michigan System; University of Michigan; State University System of Florida; University of Florida
摘要：Web search engines have become an integral part of the daily life of a knowledge worker, who depends on these search engines to retrieve relevant information from the Web or from the company's vast document databases. Current search engines are very fast in terms of their response time to a user query. But their usefulness to the user in terms of retrieval performance leaves a lot to be desired. Typically, the user has to sift through a lot of nonrelevant documents to get only a few relevant o...
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作者：Nelson, RR; Todd, PA; Wixom, BH
作者单位：University of Virginia
摘要：Understanding the successful adoption of information technology is largely based upon understanding the linkages among quality, Satisfaction, and usage. Although the satisfaction and usage constructs have been well studied in the information systems literature, there has been only limited attention to information and system quality over the past decade. To address this shortcoming, we developed a model consisting of nine fundamental determinants of quality in an information technology contexts...
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作者：Ba, S; Stallaert, J; Whinston, AB; Zhang, H
作者单位：University of Connecticut; University of Texas System; University of Texas Austin; University System of Georgia; Georgia Institute of Technology
摘要：The capabilities of network technologies have facilitated the growth of electronic commerce. Major issues-notably, security and product quality uncertainty-still pose serious challenges to the further adoption of electronic commerce. Traditional market transactions have a long history and well-understood protections for buyers and sellers. In the electronic markets, formal and informal mechanisms such as trusted third parties (TTP) have emerged trying to ensure safe transactions. In this paper...
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作者：Leimeister, JM; Ebner, W; Krcmar, H
作者单位：Technical University of Munich; Technical University of Munich
摘要：Trust provides the foundation for the successful implementation and operation of a virtual community (VC). Trust is an especially relevant success factor in online health-care communities. A look at existing communities leads to the conclusion that many VCs fail to meet requirements upon which trust is established. Based on the findings in the literature and the researchers' experience, this paper describes how trust-enabling functionalities can be systematically designed and implemented in a ...
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作者：Churilov, L; Bagirov, A; Schwartz, D; Smith, K; Dally, M
作者单位：University of Melbourne; Monash University
摘要：Data mining techniques provide a popular and powerful tool set to generate various data-driven classification systems. In this paper, we investigate the combined use of self-organizing maps (SOM) and nonsmooth nonconvex optimization techniques in order to produce a working case of a data-driven risk classification system. The optimization approach strengthens the validity of SOM results, and the improved classification system increases both the quality of prediction and the homogeneity within ...
