From ternary relationship to relational tables: a case against common beliefs

The transformation from n-ary relationships to a relational database schema has never been really fully analyzed. This paper presents one of the several ternary cases ignored by the ER-to-RM literature. The case shows that the following common belief is wrong: Given a set of FDs over a table resulting in a non-3NF situation, it is always possible to obtain a fully equivalent set of 3NF tables, without adding other restrictions than candidate keys and inclusion dependencies.Postprint (published version

Graphene: Semantically-Linked Propositions in Open Information Extraction

We present an Open Information Extraction (IE) approach that uses a two-layered transformation stage consisting of a clausal disembedding layer and a phrasal disembedding layer, together with rhetorical relation identification. In that way, we convert sentences that present a complex linguistic structure into simplified, syntactically sound sentences, from which we can extract propositions that are represented in a two-layered hierarchy in the form of core relational tuples and accompanying contextual information which are semantically linked via rhetorical relations. In a comparative evaluation, we demonstrate that our reference implementation Graphene outperforms state-of-the-art Open IE systems in the construction of correct n-ary predicate-argument structures. Moreover, we show that existing Open IE approaches can benefit from the transformation process of our framework.Comment: 27th International Conference on Computational Linguistics (COLING 2018

Transforming N-ary relationships to database schemas: an old and forgotten problem

The N-ary relationships, have been traditionally a source of confusion and still are. One important source of confusion is that the term cardinality in a relationship has several interpretations, two of them being very popular. But none of the two approaches, nor the two together, allow us to express all the possible cardinality patterns. The transformations from all the possible relationships to database schemas have never been described by the existing literature. Using the 14 ternary patterns as example, we discuss these transformations particularly the transformations from the patterns ignored in the literature.Postprint (published version

Revealing structure-function relationships in functional flow networks via persistent homology

Complex networks encountered in biology are often characterized by significant structural diversity. Whether it be differences in the three-dimensional structure of allosteric proteins, or the variation among the micro-scale structures of organisms' cerebral vasculature systems, identifying relationships between structure and function often poses a difficult challenge. Here we showcase an approach to characterizing structure-function relationships in complex networks applied in the context of flow networks tuned to perform specific functions. Using persistent homology, we analyze flow networks tuned to perform complex multifunctional tasks, answering the question of how local changes in the network structure coordinate to create functionality at at the scale of the entire network. We find that the response of such networks encodes hidden topological features - sectors of uniform pressure - that are not apparent in the underlying network architectures, Regardless of differences in local connectivity, these features provide a universal topological description for all networks that perform these types of functions. We show that these features correlate strongly with the tuned response, providing a clear topological relationship between structure and function and structural insight into the limits of multifunctionality.Comment: 22 pages (double column), 12 figure

Finding Temporally Consistent Occlusion Boundaries in Videos using Geometric Context

We present an algorithm for finding temporally consistent occlusion boundaries in videos to support segmentation of dynamic scenes. We learn occlusion boundaries in a pairwise Markov random field (MRF) framework. We first estimate the probability of an spatio-temporal edge being an occlusion boundary by using appearance, flow, and geometric features. Next, we enforce occlusion boundary continuity in a MRF model by learning pairwise occlusion probabilities using a random forest. Then, we temporally smooth boundaries to remove temporal inconsistencies in occlusion boundary estimation. Our proposed framework provides an efficient approach for finding temporally consistent occlusion boundaries in video by utilizing causality, redundancy in videos, and semantic layout of the scene. We have developed a dataset with fully annotated ground-truth occlusion boundaries of over 30 videos ($5000 frames). This dataset is used to evaluate temporal occlusion boundaries and provides a much needed baseline for future studies. We perform experiments to demonstrate the role of scene layout, and temporal information for occlusion reasoning in dynamic scenes.Comment: Applications of Computer Vision (WACV), 2015 IEEE Winter Conference o

A yield curve perspective on uncovered interest parity

This article uses a dynamic multi-factor model of the yield curve with a rational-expectations, general-equilibrium-economy foundation to investigate the uncovered interest parity hypothesis(UIPH). The yield curve model is used to decompose the interest rate data used in the UIPH regressions into components that reflect rationally-based expectations of the cyclical and fundamental components of the underlying economy. The UIPH is not rejected based on the fundamental components of interest rates, but is soundly rejected based on the cyclical components. These results provide empirical support for suggestions in the existing theoretical literature that rationally-based interest rate and exchange rate dynamics associated with cyclical inter-linkages between the economy and financial markets may contribute materially to the UIPH puzzle