Interpretable Facial Relational Network Using Relational Importance

Analyzing Correlation between Internationalization Orientation and Social Network

 The research on social networks and collaborative strategies has highlighted from the mid of 1980 which has contributed to the success and development of firms. The relationship and communication with trade partners in overseas help success of firms in entering to foreign markets and improve new partners and new markets abroad. Doing firm internationalization in foreign countries faces some ba...

Induction of Interpretable Possibilistic Logic Theories from Relational Data

The field of Statistical Relational Learning (SRL) is concerned with learning probabilistic models from relational data. Learned SRL models are typically represented using some kind of weighted logical formulas, which make them considerably more interpretable than those obtained by e.g. neural networks. In practice, however, these models are often still difficult to interpret correctly, as they...

Introducing a Relational Network DEA Model with Stochastic Intermediate measures for Portfolio Optimization

Modelling Relational Data using Bayesian Clustered Tensor Factorization

We consider the problem of learning probabilistic models for complex relational structures between various types of objects. A model can help us “understand” a dataset of relational facts in at least two ways, by finding interpretable structure in the data, and by supporting predictions, or inferences about whether particular unobserved relations are likely to be true. Often there is a tradeoff...

Revenue - Profit Measurement in Data Envelopment Analysis with Dynamic Network Structures: A Relational Model

The correlated models are introduced in this article regarding revenue efficiency and profit efficiency in dynamic network production systems. The proposed models are not only applicable in measuring efficiency of divisional, periodical and overall efficiencies, but recognizing the exact sources of inefficiency with respect to revenue and profit efficiencies. Two numerical examples, consisting ...