Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases including indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for efficiently searching uncertain categorical data over distributed environments. We address two kinds of query over the distributed un...

The ethical constraints forced on an investment fund satisfy the fulfilment of humanitarian aims but may lower the investment profitability. Hence, when we measure the performance of ethical mutual funds we cannot disregard the ethical component. In this contribution we propose a performance indicator which considers the expected return, the investment risk, the ethical component and the subscr...

The dataset you’ll examine is from a study by the California Department of Corrections (CDC) on the effectiveness of prisoner placement, and the likelihood of misconduct while incarcerated. Upon admission to a California prison, an inmate is given a questionnaire. The score on this questionnaire determines which level of security (Level I is the lightest security, Level IV the heaviest) to whic...

This paper presents a method of learning distributed representation for multi-field categorical data, which is a common data format with various applications such as recommender systems, social link prediction, and computational advertising. The success of non-linear models, e.g., factorisation machines, boosted trees, has proved the potential of exploring the interactions among inter-field cat...

The dataset you’ll examine is from a study by the California Department of Corrections (CDC) on the effectiveness of prisoner placement, and the likelihood of misconduct while incarcerated. Upon admission to a California prison, an inmate is given a questionnaire. The score on this questionnaire determines which level of security (Level I is the lightest security, Level IV the heaviest) to whic...

Global models of a dataset reflect not only the large scale structure of the data distribution, they also reflect small(er) scale structure. Hence, if one wants to see the large scale structure, one should somehow subtract this smaller scale structure from the model. While for some kinds of model – such as boosted classifiers – it is easy to see the “important” components, for many kind of mode...

We introduce MD sketches which are a particular kind of Finite Sum sketches Two interesting results about MD sketches are proved First we show that given two MD sketches it is algorithmically decidable whether their model categories are equivalent Next we show that data speci cations as used in database design and software engineering can be translated to MD sketches As a corollary we obtain th...