A probabilistic database extension

Data exchange between embedded systems and other small or large computing devices increases. Since data in different data sources may refer to the same real world objects, data cannot simply be merged. Furthermore, in many situations, conflicts in data about the same real world objects need to be resolved without interference from a user. In this report, we report on an attempt to make a RDBMS probabilistic, i.e., data in a relation represents all possible views on the real world, in order to achieve unattended data integration. We define a probabilistic relational data model and review standard SQL query primitives in the light of probabilistic data. It appears that thinking in terms of `possible worlds¿ is powerful in determining the proper semantics of these query primitives

Switching Between Expectation Processes in the Foreign Exchange Market: A Probabilistic Approach Using Survey Data

This paper relaxes a fundamental hypothesis commonly accepted in the expectation formation literature: expectations are, unchangingly, either rational or generated by one of the three simple extrapolative, regressive or adaptive processes. Using expectations survey data provided by Consensus Forecasts on six European exchange rates against the US Dollar, we find that the rational expectations hypothesis is rejected at the aggregate level. By implementing a switching regression methodology with stochastic choice of regime, we show that the expectation generating process is given at any time by some combination of the three simple processes. An interpretation of this framework in terms of economically rational expectations is suggested.expectation formation; switching-regime; exchange rates; survey data; cost and advantage analysis

User Feedback in Probabilistic XML

Data integration is a challenging problem in many application areas. Approaches mostly attempt to resolve semantic uncertainty and conflicts between information sources as part of the data integration process. In some application areas, this is impractical or even prohibitive, for example, in an ambient environment where devices on an ad hoc basis have to exchange information autonomously. We have proposed a probabilistic XML approach that allows data integration without user involvement by storing semantic uncertainty and conflicts in the integrated XML data. As a\ud consequence, the integrated information source represents\ud all possible appearances of objects in the real world, the\ud so-called possible worlds.\ud \ud In this paper, we show how user feedback on query results\ud can resolve semantic uncertainty and conflicts in the\ud integrated data. Hence, user involvement is effectively postponed to query time, when a user is already interacting actively with the system. The technique relates positive and\ud negative statements on query answers to the possible worlds\ud of the information source thereby either reinforcing, penalizing, or eliminating possible worlds. We show that after repeated user feedback, an integrated information source better resembles the real world and may converge towards a non-probabilistic information source

Taming Data Explosion in Probabilistic Information Integration

Data integration has been a challenging problem for decades. In an ambient environment, where many autonomous devices have their own information sources and network connectivity is ad hoc and peer-to-peer, it even becomes a serious bottleneck. To enable devices to exchange information without the need for interaction with a user at data integration time and without the need for extensive semantic annotations, a probabilistic approach seems rather promising. It simply teaches the device how to cope with the uncertainty occurring during data integration. Unfortunately, without any kind of world knowledge, almost everything becomes uncertain, hence maintaining all possibilities produces huge integrated information sources. In this paper, we claim that only very simple and generic rules are enough world knowledge to drastically reduce the amount of uncertainty, hence to tame the data explosion to a manageable size

Large Swings in Currencies driven by Fundamentals

Exchange rate returns are fat-tailed distributed. We provide evidence that the apparent non-normality derives from the behavior of macroeconomic fundamentals. Economic and probabilistic arguments are offered for such a relationship. Empirical support is given by testing against normality and through investigating the tail shapes of the fundamentals' distributions. The currently available data sets on floating exchange rates permit a clearer picture than the relatively short spans with macroeconomic data available previously

Cluster Analysis of Business Data

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.In this work, classical as well as probabilistic hierarchical clustering models are used to look for typologies of variables in classical data, typologies of groups of individuals in a classical three-way data table, and typologies of groups of individuals in a symbolic data table. The data are issued from a questionnaire on business area in order to evaluate the quality and satisfaction with the services provided to customers by an automobile company. The Ascendant Hierarchical Cluster Analysis (AHCA) is based, respectively, on the basic affinity coefficient and on extensions of this coefficient for the cases of a classical three-way data table and a symbolic data table, obtained from the weighted generalized affinity coefficient. The probabilistic aggregation criteria used, under the probabilistic approach named VL methodology (V for Validity, L for Linkage), resort essentially to probabilistic notions for the definition of the comparative functions. The validation of the obtained partitions is based on the global statistics of levels (STAT)

Kinetic models of immediate exchange

We propose a novel kinetic exchange model differing from previous ones in two main aspects. First, the basic dynamics is modified in order to represent economies where immediate wealth exchanges are carried out, instead of reshufflings or uni-directional movements of wealth. Such dynamics produces wealth distributions that describe more faithfully real data at small values of wealth. Secondly, a general probabilistic trading criterion is introduced, so that two economic units can decide independently whether to trade or not depending on their profit. It is found that the type of the equilibrium wealth distribution is the same for a large class of trading criteria formulated in a symmetrical way with respect to the two interacting units. This establishes unexpected links between and provides a microscopic foundations of various kinetic exchange models in which the existence of a saving propensity is postulated. We also study the generalized heterogeneous version of the model in which units use different trading criteria and show that suitable sets of diversified parameter values with a moderate level of heterogeneity can reproduce realistic wealth distributions with a Pareto power law.Comment: 10 pages, 7 figure