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The Provenance Ontology (PROV-O) is a World Wide Web Consortium (W3C) recommended ontology used to structure data about provenance across a wide variety of domains. Basic Formal Ontology (BFO) is a top-level ontology ISO/IEC standard used…

Many platforms for benchmarking optimization algorithms offer users the possibility of sharing their experimental data with the purpose of promoting reproducible and reusable research. However, different platforms use different data models…

Neural and Evolutionary Computing · Computer Science 2021-04-27 Ana Kostovska , Diederick Vermetten , Carola Doerr , Sašo Džeroski , Panče Panov , Tome Eftimov

The ever-increasing amount of data in biomedical research, and in cancer research in particular, needs to be managed to support efficient data access, exchange and integration. Existing software infrastructures, such caGrid, support access…

Artificial Intelligence · Computer Science 2010-12-30 Alejandra Gonzalez-Beltran , Ben Tagger , Anthony Finkelstein

Ontology-mediated query answering (OMQA) is a promising approach to data access and integration that has been actively studied in the knowledge representation and database communities for more than a decade. The vast majority of work on…

Logic in Computer Science · Computer Science 2020-09-22 Meghyn Bienvenu , Quentin Manière , Michaël Thomazo

Generating vector representations (embeddings) of OWL ontologies is a growing task due to its applications in predicting missing facts and knowledge-enhanced learning in fields such as bioinformatics. The underlying semantics of OWL…

Logic in Computer Science · Computer Science 2024-11-07 Fernando Zhapa-Camacho , Robert Hoehndorf

In Ontology Based Data Access (OBDA) users pose SPARQL queries over an ontology that lies on top of relational datasources. These queries are translated on-the-fly into SQL queries by OBDA systems. Standard SPARQL-to-SQL translation…

Databases · Computer Science 2016-05-17 Dag Hovland , Davide Lanti , Martin Rezk , Guohui Xiao

As database query processing techniques are being used to handle diverse workloads, a key emerging challenge is how to efficiently handle multi-way join queries containing multiple many-to-many joins. While uncommon in traditional…

Databases · Computer Science 2025-05-20 Hasara Kalumin , Amol Deshpande

Current methods for embedding-based query answering over incomplete Knowledge Graphs (KGs) only focus on inductive reasoning, i.e., predicting answers by learning patterns from the data, and lack the complementary ability to do deductive…

Artificial Intelligence · Computer Science 2023-09-01 Medina Andresel , Trung-Kien Tran , Csaba Domokos , Pasquale Minervini , Daria Stepanova

As declarative query processing techniques expand in scope --- to the Web, data streams, network routers, and cloud platforms --- there is an increasing need for adaptive query processing techniques that can re-plan in the presence of…

Databases · Computer Science 2014-09-23 Mengmeng Liu , Zachary G. Ives , Boon Thau Loo

In recent years, \emph{learned cardinality estimation} has emerged as an alternative to traditional query optimization methods: by training machine learning models over observed query performance, learned cardinality estimation techniques…

Databases · Computer Science 2023-12-05 Peizhi Wu , Ryan Marcus , Zachary G. Ives

Use case specifications have successfully been used for requirements description. They allow joining, in the same modeling space, the expectations of the stakeholders as well as the needs of the software engineer and analyst involved in the…

Software Engineering · Computer Science 2014-04-04 Rui Couto , António Nestor Ribeiro , José Creissac Campos

Enterprises are creating domain-specific knowledge graphs by curating and integrating their business data from multiple sources. The data in these knowledge graphs can be described using ontologies, which provide a semantic abstraction to…

Databases · Computer Science 2020-10-06 Chuan Lei , Rana Alotaibi , Abdul Quamar , Vasilis Efthymiou , Fatma Özcan

Semantic annotation is fundamental to deal with large-scale lexical information, mapping the information to an enumerable set of categories over which rules and algorithms can be applied, and foundational ontology classes can be used as a…

Computation and Language · Computer Science 2018-06-21 Vivian S. Silva , André Freitas , Siegfried Handschuh

We introduce ontology-mediated planning, in which planning problems are combined with an ontology. Our formalism differs from existing ones in that we focus on a strong separation of the formalisms for describing planning problems and…

Artificial Intelligence · Computer Science 2024-08-15 Tobias John , Patrick Koopmann

Reasoning over OWL 2 is a very expensive task in general, and therefore the W3C identified tractable profiles exhibiting good computational properties. Ontological reasoning for many fragments of OWL 2 can be reduced to the evaluation of…

Artificial Intelligence · Computer Science 2020-03-24 Mario Alviano , Marco Manna

Efficiently querying Description Logic (DL) ontologies is becoming a vital task in various data-intensive DL applications. Considered as a basic service for answering object queries over DL ontologies, instance checking can be realized by…

Artificial Intelligence · Computer Science 2015-02-27 Jia Xu , Patrick Shironoshita , Ubbo Visser , Nigel John , Mansur Kabuka

With the more and more growing demand for semantic Web services over large databases, an efficient evaluation of Datalog queries is arousing a renewed interest among researchers and industry experts. In this scenario, to reduce memory…

Artificial Intelligence · Computer Science 2020-02-19 Alessio Fiorentino , Nicola Leone , Marco Manna , Simona Perri , Jessica Zangari

The W3C Web Ontology Language (OWL) is a powerful knowledge representation formalism at the basis of many semantic-centric applications. Since its unrestricted usage makes reasoning undecidable already in case of very simple tasks,…

Artificial Intelligence · Computer Science 2020-08-06 Alessio Fiorentino , Jessica Zangari , Marco Manna

Decision support is a probabilistic and quantitative method designed for modeling problems in situations with ambiguity. Computer technology can be employed to provide clinical decision support and treatment recommendations. The problem of…

Artificial Intelligence · Computer Science 2018-12-06 Ying Shen , Joël Colloc , Armelle Jacquet-Andrieu , Ziyi Guo , Yong Liu

Large Language Models (LLMs) are revolutionizing how users interact with information systems, yet their high inference cost poses serious scalability and sustainability challenges. Caching inference responses, allowing them to be retrieved…

Machine Learning · Computer Science 2026-02-16 Xutong Liu , Baran Atalar , Xiangxiang Dai , Jinhang Zuo , Siwei Wang , John C. S. Lui , Wei Chen , Carlee Joe-Wong