Schema Independent Relational Learning

Learning novel concepts and relations from relational databases is an important problem with many applications in database systems and machine learning. Relational learning algorithms learn the definition of a new relation in terms of existing relations in the database. Nevertheless, the same data set may be represented under different schemas for various reasons, such as efficiency, data quality, and usability. Unfortunately, the output of current relational learning algorithms tends to vary quite substantially over the choice of schema, both in terms of learning accuracy and efficiency. This variation complicates their off-the-shelf application. In this paper, we introduce and formalize the property of schema independence of relational learning algorithms, and study both the theoretical and empirical dependence of existing algorithms on the common class of (de) composition schema transformations. We study both sample-based learning algorithms, which learn from sets of labeled examples, and query-based algorithms, which learn by asking queries to an oracle. We prove that current relational learning algorithms are generally not schema independent. For query-based learning algorithms we show that the (de) composition transformations influence their query complexity. We propose Castor, a sample-based relational learning algorithm that achieves schema independence by leveraging data dependencies. We support the theoretical results with an empirical study that demonstrates the schema dependence/independence of several algorithms on existing benchmark and real-world datasets under (de) compositions

Relative Expressive Power of Navigational Querying on Graphs

Motivated by both established and new applications, we study navigational query languages for graphs (binary relations). The simplest language has only the two operators union and composition, together with the identity relation. We make more powerful languages by adding any of the following operators: intersection; set difference; projection; coprojection; converse; and the diversity relation. All these operators map binary relations to binary relations. We compare the expressive power of all resulting languages. We do this not only for general path queries (queries where the result may be any binary relation) but also for boolean or yes/no queries (expressed by the nonemptiness of an expression). For both cases, we present the complete Hasse diagram of relative expressiveness. In particular the Hasse diagram for boolean queries contains some nontrivial separations and a few surprising collapses.Comment: An extended abstract announcing the results of this paper was presented at the 14th International Conference on Database Theory, Uppsala, Sweden, March 201

Expanding the Direct and Indirect Effects Model of Writing (DIEW) : Reading–writing relations, and dynamic relations as a function of measurement/dimensions of written composition

Within the context of the Direct and Indirect Effects Model of Writing (Kim & Park, 2019), we examined a dynamic relations hypothesis, which contends that the relations of component skills, including reading comprehension, to written composition vary as a function of dimensions of written composition. Specifically, we investigated (a) whether higher-order cognitive skills (i.e., inference, perspective taking, and monitoring) are differentially related to three dimensions of written composition—writing quality, writing productivity, and correctness in writing; (b) whether reading comprehension is differentially related to the three dimensions of written composition after accounting for oral language, cognition, and transcription skills, and whether reading comprehension mediates the relations of discourse oral language and lexical literacy to the three dimensions of written composition; and (c) whether total effects of oral language, cognition, transcription, and reading comprehension vary for the three dimensions of written composition. Structural equation model results from 350 English-speaking second graders showed that higher-order cognitive skills were differentially related to the three dimensions of written composition. Reading comprehension was related only to writing quality, but not to writing productivity or correctness in writing, and reading comprehension differentially mediated the relations of discourse oral language and lexical literacy to writing quality. Total effects of language, cognition, transcription, and reading comprehension varied largely for the three dimensions of written composition. These results support the dynamic relation hypothesis, role of reading in writing, and the importance of accounting for dimensions of written composition in a theoretical model of writing. (PsycInfo Database Record (c) 2022 APA, all rights reserved

Function vs. Taxonomy: The Case of Fungi Mitochondria ATP Synthase Genes

We studied the relations between triplet composition of the family of mitochondrial atp6, atp8 and atp9 genes, their function, and taxonomy of the bearers. The points in 64-dimensional metric space corresponding to genes have been clustered. It was found the points are separated into three clusters corresponding to those genes. 223 mitochondrial genomes have been enrolled into the database

Computer Aided Verification of Relational Models

Binary relational algebra provides semantic foundations for major areas of computing, such as database design, state-based modeling and functional programming. Remarkably, static checking support in these areas fails to exploit the full semantic content of relations. In particular, properties such as the simplicity or injectivity of relations are not statically enforced in operations such as database queries, state transitions, or composition of functional components. When data models, their constraints and operations are represented by point-free binary relational expressions, proof obligations can be expressed as inclusions between relational expressions.We developed a type-directed, strategic term rewriting system that can be used to simplify relational proof obligations and ultimately reduce them to tautologies. Such reductions can be used to provide extended static checking for design contraints commonly found in software modeling and development.XIII Workshop Ingeniería de Software (WIS).Red de Universidades con Carreras en Informática (RedUNCI

A GENERIC MODEL FOR KNOWLEDGE BASES

A knowledge base system is a database system with logical, temporal and topological structures together with operations on these structures. vVe provide the necessary mathematical concepts for modeling such a system. These are parametrized hierarchical relations, logic functions, hierarchies of variables with their hierarchical control operators, and neighborhood/similarity structures. These concepts are then applied to define a model of a knowledge module. By composition of knowledge modules we obtain the knowledge system model

The Yale-Potsdam Stellar Isochrones (YaPSI)

We introduce the Yale-Potsdam Stellar Isochrones (YaPSI), a new grid of stellar evolution tracks and isochrones of solar-scaled composition. In an effort to improve the Yonsei-Yale database, special emphasis is placed on the construction of accurate low-mass models (Mstar < 0.6 Msun), and in particular of their mass-luminosity and mass-radius relations, both crucial in characterizing exoplanet-host stars and, in turn, their planetary systems. The YaPSI models cover the mass range 0.15 to 5.0 Msun, densely enough to permit detailed interpolation in mass, and the metallicity and helium abundance ranges [Fe/H] = -1.5 to +0.3, and Y = 0.25 to 0.37, specified independently of each other (i.e., no fixed Delta Y/Delta Z relation is assumed). The evolutionary tracks are calculated from the pre-main sequence up to the tip of the red giant branch. The isochrones, with ages between 1 Myr and 20 Gyr, provide UBVRI colors in the Johnson-Cousins system, and JHK colors in the homogeneized Bessell & Brett system, derived from two different semi-empirical Teff-color calibrations from the literature. We also provide utility codes, such as an isochrone interpolator in age, metallicity, and helium content, and an interface of the tracks with an open-source Monte Carlo Markov-Chain tool for the analysis of individual stars. Finally, we present comparisons of the YaPSI models with the best empirical mass- luminosity and mass-radius relations available to date, as well as isochrone fitting of well-studied steComment: 17 pages, 14 figures; accepted for publication in the Astrophysical Journa