702 research outputs found
A Possibilistic Query Translation Approach for Cross-Language Information Retrieval
International audienceIn this paper, we explore several statistical methods to find solutions to the problem of query translation ambiguity. Indeed, we propose and compare a new possibilistic approach for query translation derived from a probabilistic one, by applying a classical probability-possibility transformation of probability distributions, which introduces a certain tolerance in the selection of word translations. Finally, the best words are selected based on a similarity measure. The experiments are performed on CLEF-2003 French-English CLIR collection, which allowed us to test the effectiveness of the possibilistic approach
Some applications of possibilistic mean value, variance, covariance and correlation
In 2001 we introduced the notions of possibilistic mean value and variance of fuzzy numbers. In this paper we list some works that use these notions. We shall mention some application areas as wel
A possibilistic framework for constraint-based metabolic flux analysis
<p>Abstract</p> <p>Background</p> <p>Constraint-based models allow the calculation of the metabolic flux states that can be exhibited by cells, standing out as a powerful analytical tool, but they do not determine which of these are likely to be existing under given circumstances. Typical methods to perform these predictions are (a) flux balance analysis, which is based on the assumption that cell behaviour is optimal, and (b) metabolic flux analysis, which combines the model with experimental measurements.</p> <p>Results</p> <p>Herein we discuss a possibilistic framework to perform metabolic flux estimations using a constraint-based model and a set of measurements. The methodology is able to handle inconsistencies, by considering sensors errors and model imprecision, to provide rich and reliable flux estimations. The methodology can be cast as linear programming problems, able to handle thousands of variables with efficiency, so it is suitable to deal with large-scale networks. Moreover, the possibilistic estimation does not attempt necessarily to predict the actual fluxes with precision, but rather to exploit the available data â even if those are scarce â to distinguish possible from impossible flux states in a gradual way.</p> <p>Conclusion</p> <p>We introduce a possibilistic framework for the estimation of metabolic fluxes, which is shown to be flexible, reliable, usable in scenarios lacking data and computationally efficient.</p
Application of DEO Method to Solving Fuzzy Multiobjective Optimal Control Problem
In the present paper a problem of optimal control for a single-product dynamical macroeconomic model is considered. In this model gross domestic product is divided into productive consumption, gross investment, and nonproductive consumption. The model is described by a fuzzy differential equation (FDE) to take into account imprecision inherent in the dynamics that may be naturally conditioned by influence of various external factors, unforeseen contingencies of future, and so forth. The considered problems are characterized by four criteria and by several important aspects. On one hand, the problem is complicated by the presence of fuzzy uncertainty as a result of a natural imprecision inherent in information about dynamics of real-world systems. On the other hand, the number of the criteria is not small and most of them are integral criteria. Due to the above mentioned aspects, solving the considered problem by using convolution of criteria into one criterion would lead to loss of information and also would be counterintuitive and complex. We applied DEO (differential evolution optimization) method to solve the considered problem
Towards an intelligent possibilistic web information retrieval using multiagent system.
PURPOSE - The purpose of this paper is to make a scientific contribution to web information retrieval (IR). Design/methodolog y/approach â A multiagent system for web IR is proposed based on new technologies: Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). This system is based on a possibilistic qualitative approach which extends the quantitative one. FINDINGS â The paper finds that the relevance of the order of documents changes while passing from a profile to another. Even if the selected terms tend to select the relevant document, these terms are not the most frequent of the document. This criterion shows the asset of the qualitative approach of the SARIPOD system in the selection of relevant documents. The insertion of the factors of preference between query terms in the calculations of the possibility and the necessity consists in increasing the scores of possibilistic relevance of the documents containing these terms with an aim of penalizing the scores of relevance of the documents not containing them. The penalization and the increase in the scores are proportional to the capacity of the terms to discriminate between the documents of the collection. RESEARCH LIMITATIONS/IMPLICATIONS â It is planned to extend the tests of the SARIPOD system to other grammatical categories, like refining the approach for the substantives by considering for example, the verbal occurrences in names definitions, etc. Also, it is planned to carry out finer measurements of the performances of SARIPOD system by extending the tests with other types of web documents. PRACTICAL IMPLICATIONS â The system can be useful to help research students find their relevant scientific papers. It must be located in the document server of any research laboratory. ORIGINALITY/VALUE â The paper presents SARIPOD, a new qualitative possibilistic model for web IR using multiagent syste
THINGS FROM THE FUTURE How can we crowdsource innovation foresight with games?
In the current world uncertainty is more dominant than it used to be. One of the key forces for constant change is innovation. Innovations can be radical and create surprising effects. Can there be ways of anticipating these unforeseen effects of innovation? Or can the course of future innovations be managed somehow? Innovation foresight processes are required to communicate between different stakeholders on an extensive scale to be able to build comprehensive and understandable future options. Knowledge on future and innovation is no more the exclusive right of experts. This study tries to find new ways of engaging people with the innovation foresight work as well as get new audiences to participate in it. Games and crowdsourcing are two possible solutions to this.
Theories covering innovation, foreisght and crowdsourcing are plentiful but scattered, and do not form a coherent framework for innovation foresight. Study is approaching the research topic from two perspectives: what kind of innovation foresight knowledge can we create with games, and what innovation foresight activities can we crowdsource with games? For these targets study has used two different methods, an innovation game case study experiment and a questionnaire targeted to Finnish innovation experts. Game case study consisted of a foresight analysis of 310 âfuture thingâ ideas generated with an innovation card game. The results revealed that games can enhance the creativity of the players and generate many unexpected uses of future technologies and services. Ideas were also rich with future hopes and fears and they had multidimensional content including different PESTE-variables. Questionnaire was targeted to map views related to the usability of games in different phases of the innovation foresight process. According to responses gaming can be used to observe weak signals, to form wild cards, perceive hopes and fears, and to develop new visions for the future. But games are not seen as suitable for decision-making nor forecasting future trends. Crowdsourcing can enhance the âcrowd wisdomâ of the foresight process. Crowd wisdom means that groups are often smarter than the smartest people in them. This phenomenon is based on the thought that âno one knows everything, but everyone knows somethingâ.
The challenge in crowdsourcing is to motivate people to participate and engage. Games can be a powerful solution to innovation foresight motivation challenge, and they may also generate different solutions than other methods. But games cannot replace the foresight process. To subject foresight to games and gamification would take too many resources, be expensive, difficult to manage, and results would be risky. Crowdsourcing innovation foresight can often be carried out more effectively when using existing social media platforms such as Facebook, Twitter etc. instead of games. In any case, crowd wisdom is too valuable resource not to be exploited in foresight.siirretty Doriast
Low rank surrogates for polymorphic fields with application to fuzzy-stochastic partial differential equations
We consider a general form of fuzzy-stochastic PDEs depending on the interaction of probabilistic
and non-probabilistic ("possibilistic") influences. Such a combined modelling of aleatoric
and epistemic uncertainties for instance can be applied beneficially in an engineering context for
real-world applications, where probabilistic modelling and expert knowledge has to be accounted
for. We examine existence and well-definedness of polymorphic PDEs in appropriate function
spaces. The fuzzy-stochastic dependence is described in a high-dimensional parameter space,
thus easily leading to an exponential complexity in practical computations.
To aleviate this severe obstacle in practise, a compressed low-rank approximation of the problem
formulation and the solution is derived. This is based on the Hierarchical Tucker format which
is constructed with solution samples by a non-intrusive tensor reconstruction algorithm. The performance
of the proposed model order reduction approach is demonstrated with two examples.
One of these is the ubiquitous groundwater flow model with Karhunen-Loeve coefficient field
which is generalized by a fuzzy correlation length
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