Titlebook: Database and Expert Systems Applications; 25th International C Hendrik Decker,Lenka Lhotská,Roland R. Wagner Conference proceedings 2014 Sp

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Designing Incentives for Community-Based Mobile Crowdsourcing Service Architecturen strategies of community-based mobile crowdsourcing services explicitly consider the tradeoff among multiple incentives. This is significantly different from the design in traditional crowdsourcing services because their designers usually consider only a few incentives when designing respective soc

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Fraud Indicators Applied to Legal Entities: An Empirical Ranking Approachcores are subsequently combined and weighed into a total risk score that indicates whether a legal person is likely to commit fraud based on all risk indicators. This contribution reports on our two ranking approaches: one based on the empirical probabilities of the indicators and the other based on

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A Probabilistic Approach to Detect Local Dependencies in Streams correlated stocks for an interesting event in the financial system. We apply this framework to two real data sets to demonstrate its advantages compared with the Principal Component Analysis (PCA) based method [16] and the naive local Pearson implementation.

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Inferring Topic-Level Influence from Network Datagth among the users for each topic. Experimental results on two real world datasets demonstrate the effectiveness of our method. Further, we show that the proposed topic-level influence network can improve the precision of user behavior prediction and is useful for influence maximization.

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Helena Holmström Olsson,Jan Boschut losing much classification performance, when compared with ensemble classification paradigms. Further experiment results show that Arguing Prism out-performs comparable classification paradigms in presence of inconsistent data, due to the advantages offered by argumentation.