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Lifted Relational Neural Networks (LRNNs) describe relational domains using weighted first-order rules which act as templates for constructing feed-forward neural networks. While previous work has shown that using LRNNs can lead to…

Machine Learning · Computer Science 2017-10-09 Gustav Sourek , Martin Svatos , Filip Zelezny , Steven Schockaert , Ondrej Kuzelka

We study the problem of computing a conjunctive query q in parallel, using p of servers, on a large database. We consider algorithms with one round of communication, and study the complexity of the communication. We are especially…

Databases · Computer Science 2014-01-10 Paul Beame , Paraschos Koutris , Dan Suciu

Semantic parsing methods for converting text to SQL queries enable question answering over structured data and can greatly benefit analysts who routinely perform complex analytics on vast data stored in specialized relational databases.…

Databases · Computer Science 2025-09-25 Mounica Maddela , Lingjue Xie , Daniel Preotiuc-Pietro , Mausam

We perform a fundamental investigation of the complexity of conjunctive query evaluation from the perspective of parameterized complexity. We classify sets of boolean conjunctive queries according to the complexity of this problem. Previous…

Computational Complexity · Computer Science 2013-06-26 Hubie Chen , Moritz Müller

We present LinkQ, a system that leverages a large language model (LLM) to facilitate knowledge graph (KG) query construction through natural language question-answering. Traditional approaches often require detailed knowledge of a graph…

Computation and Language · Computer Science 2025-02-11 Harry Li , Gabriel Appleby , Ashley Suh

Answering complex logical queries on incomplete knowledge graphs (KGs) with missing edges is a fundamental and important task for knowledge graph reasoning. The query embedding method is proposed to answer these queries by jointly encoding…

Computation and Language · Computer Science 2022-04-28 Jiaxin Bai , Zihao Wang , Hongming Zhang , Yangqiu Song

Data in tabular format is frequently occurring in real-world applications. Graph Neural Networks (GNNs) have recently been extended to effectively handle such data, allowing feature interactions to be captured through representation…

Machine Learning · Computer Science 2024-08-14 Amr Alkhatib , Sofiane Ennadir , Henrik Boström , Michalis Vazirgiannis

In recent years, the problem of association rule mining in transactional data has been well studied. We propose to extend the discovery of classical association rules to the discovery of association rules of conjunctive queries in arbitrary…

Databases · Computer Science 2007-05-23 Bart Goethals , Jan Van den Bussche

Ontology-Mediated Query Answering (OMQA) is a well-established framework to answer queries over an RDFS or OWL Knowledge Base (KB). OMQA was originally designed for unions of conjunctive queries (UCQs), and based on certain answers. More…

Databases · Computer Science 2019-11-22 Julien Corman , Guohui Xiao

The resilience of a Boolean query is the minimum number of tuples that need to be deleted from the input tables in order to make the query false. A solution to this problem immediately translates into a solution for the more widely known…

Databases · Computer Science 2020-06-17 Cibele Freire , Wolfgang Gatterbauer , Neil Immerman , Alexandra Meliou

A quantum algorithm for combinatorial search is presented that provides a simple framework for utilizing search heuristics. The algorithm is evaluated in a new case that is an unstructured version of the graph coloring problem. It performs…

Quantum Physics · Physics 2009-10-06 Tad Hogg

Answering complex questions is a time-consuming activity for humans that requires reasoning and integration of information. Recent work on reading comprehension made headway in answering simple questions, but tackling complex questions is…

Computation and Language · Computer Science 2018-03-20 Alon Talmor , Jonathan Berant

We examine the problem of question answering over knowledge graphs, focusing on simple questions that can be answered by the lookup of a single fact. Adopting a straightforward decomposition of the problem into entity detection, entity…

Computation and Language · Computer Science 2018-06-07 Salman Mohammed , Peng Shi , Jimmy Lin

We study the question of when we can provide direct access to the k-th answer to a Conjunctive Query (CQ) according to a specified order over the answers in time logarithmic in the size of the database, following a preprocessing step that…

Databases · Computer Science 2022-11-30 Nofar Carmeli , Nikolaos Tziavelis , Wolfgang Gatterbauer , Benny Kimelfeld , Mirek Riedewald

Learning constraint networks is known to require a number of membership queries exponential in the number of variables. In this paper, we learn constraint networks by asking the user partial queries. That is, we ask the user to classify…

This work deals with the challenge of learning and reasoning over multi-modal multi-hop question answering (QA). We propose a graph reasoning network based on the semantic structure of the sentences to learn multi-source reasoning paths and…

Computation and Language · Computer Science 2025-01-09 Navya Yarrabelly , Saloni Mittal

We consider open-domain queston answering (QA) where answers are drawn from either a corpus, a knowledge base (KB), or a combination of both of these. We focus on a setting in which a corpus is supplemented with a large but incomplete KB,…

Computation and Language · Computer Science 2019-04-23 Haitian Sun , Tania Bedrax-Weiss , William W. Cohen

The Chinese Remainder Theorem for the integers says that every system of congruence equations is solvable as long as the system satisfies an obvious necessary condition. This statement can be generalized in a natural way to arbitrary…

Computational Complexity · Computer Science 2023-07-07 Miguel Campercholi , Diego Castaño , Gonzalo Zigarán

Given unstructured text, Large Language Models (LLMs) are adept at answering simple (single-hop) questions. However, as the complexity of the questions increase, the performance of LLMs degrade. We believe this is due to the overhead…

Computation and Language · Computer Science 2024-06-11 Pranoy Panda , Ankush Agarwal , Chaitanya Devaguptapu , Manohar Kaul , Prathosh A P

Computational complexity is a core theory of computer science, which dictates the degree of difficulty of computation. There are many problems with high complexity that we have to deal, which is especially true for AI. This raises a big…

Computational Complexity · Computer Science 2023-01-10 Chuyu Xiong