20 papers · ranked by Valyu relevance
Paul C. Bogdan, Roberto Cabeza, Simon W. Davis
How the brain organizes semantic information is one of the most challenging and expansive questions in cognitive neuroscience. To shed light on this issue, prior studies have attempted to decode how the brain represents concepts. We instead examined how relational information is encoded, which we pursued by submitting…
Natalia I. Córdova, Nicholas B. Turk-Browne, Mariam Aly
Hippocampal episodic memory is fundamentally relational, consisting of links between events and the spatial and temporal contexts in which they occurred. Such relations are also important over much shorter time periods, during online visual perception. For example, how do we assess the relative spatial positions of…
Luke J. Hearne, Conor Robinson, Luca Cocchi, Takuya Ito
Relational reasoning—the capacity to understand how elements relate to one another—is a defining feature of human intelligence, yet its computational basis remains unclear. Here, we combined human neuroimaging (7T fMRI) and artificial neural network modeling to examine relational reasoning in biological and artificial…
Kenneth Kay, Natalie Biderman, Ramin Khajeh, Manuel Beiran + 6 more
Relational cognition — the ability to infer relationships that generalize to novel combinations of objects — is fundamental to human and animal intelligence. Despite this importance, it remains unclear how relational cognition is implemented in the brain due in part to a lack of hypotheses and predictions at the levels…
Patricia A Alexander
This article offers an overview of the nature and role of relational thinking and relational reasoning in human learning and performance, both of which pertain to the discernment of meaningful patterns within any informational stream. Distinctions between thinking and reasoning relationally are summarized, along with…
Ben Perach, Ronny Ronen, Shahar Kvatinsky
—Online Analytical Processing (OLAP) for relational databases is a business decision support application. The application receives queries about the business database, usually requesting to summarize many database records, and produces few results. Existing OLAP requires transferring a large amount of data between the…
Hagit Magen, Michal Tomer-Offen
In many circumstances in everyday life, individuals offload information to external stores (e.g., shopping lists) to compensate for limitations in internal memory. When saving information externally, individuals tend to refrain from actively encoding an additional internal copy of the information, leading to a…
Slavko Žitnik, Marinka Žitnik, Blaž Zupan, Marko Bajec
Background Relation extraction is an essential procedure in literature mining. It focuses on extracting semantic relations between parts of text, called mentions. Biomedical literature includes an enormous amount of textual descriptions of biological entities, their interactions and results of related experiments. To…
Xuesong Du, Pei Sun
Relational integration is essential for learning, working, and living, as we must encode enormous volumes of information and extract their relations to construct knowledge about the environment. Recent research hints that generating distant analogies can temporarily facilitate learners’ state-based relational…
Changjae Lee, Zhuoyue Zhao, Xiong Jinjun
The emergence of large-language models (LLMs) has enabled a new class of semantic data processing systems (SDPSs) to support declarative queries against unstructured documents. Existing SDPSs are, however, lacking a unified algebraic foundation, making their queries difficult to compose, reason, and optimize. We…
Michael Statt, Kristopher Brown, Santosh Suram, Linda Hung + 3 more
In this work, we present DBgen, a Python library that provides a framework for defining extract-transform-load (ETL) pipelines to create and populate SQL databases. DBgen is most useful when the underlying data has complex relationships, requires multi-step analysis, is large-scale, and the type of data being collected…
Mohamed S. Hassan, Tatiana Kuznetsova, Hyun Chai Jeong, Walid G. Aref + 1 more
'Walid G. Aref' 'Mohammad Sadoghi'] The plethora of graphs and relational data give rise to many interesting graph-relational queries in various domains, e.g., finding related proteins satisfying relational predicates in a biological network. The maturity of RDBMSs motivated academia and industry to invest efforts in…
Leonidas A. A. Doumas, Guillermo Puebla, Andrea E. Martin
How a system represents information tightly constrains the kinds of problems it can solve. Humans routinely solve problems that appear to require structured representations of stimulus properties and relations. Answering the question of how we acquire these representations has central importance in an account of human…
Christopher R. Aberger, Susan Tu, Kunle Olukotun, Christopher Ré
There are two types of high-performance graph processing engines: low- and high-level engines. Low-level engines (Galois, PowerGraph, Snap) provide optimized data structures and computation models but require users to write low-level imperative code, hence ensuring that efficiency is the burden of the user. In…
Tobias Grubenmann, Jens Lehmann
Spatial data is ubiquitous in our data-driven society. The Logic Programming community has been investigating the use of spatial data in different settings. Despite the success of this research, the Geographic Information System (GIS) community has rarely made use of these new approaches. This has mainly two reasons.…
Giuseppe Fusco, Lerina Aversano, Sebastian Ventura
Integrating data from multiple heterogeneous data sources entails dealing with data distributed among heterogeneous information sources, which can be structured, semi-structured or unstructured, and providing the user with a unified view of these data. Thus, in general, gathering information is challenging, and one of…
Amin Beheshti, Boualem Benatallah, Hamid Reza Motahari‐Nezhad, Samira Ghodratnama + 1 more
'Samira Ghodratnama' 'Farhad Amouzgar'] Abstract. In modern enterprises, Business Processes (BPs) are realized over a mix of workflows, IT systems, Web services and direct collaborations of people. Accordingly, process data (i.e., BP execution data such as logs containing events, interaction messages and other process…
Aaron Liu, Myeongyeon Lee, Rahul Venkatesh, Jessica Bonsu + 4 more
Polymer-based semiconductors and organic electronics encapsulate a significant research thrust for informatics-driven materials development. However, device measurements are described by a complex array of design and parameter choices, many of which are sparsely reported. For example, the mobility of a polymer-based…
Naoual El aboudi, Laila Benhlima
The growing amount of data in healthcare industry has made inevitable the adoption of big data techniques in order to improve the quality of healthcare delivery. Despite the integration of big data processing approaches and platforms in existing data management architectures for healthcare systems, these architectures…
Mahnoor Zulfiqar, Michael R. Crusoe, Birgitta König-Ries, Christoph Steinbeck + 2 more
Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for…