Schema.org as a Description Logic

Authors: Andre Hernich, Carsten Lutz, Ana Ozaki, Frank Wolter

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Our main aim is to investigate the complexity of querying data in the presence of schema.org-ontologies, where the data is the markup that was extracted from webpages. While answering queries over such data is the main reasoning task that arises in Schema.org applications and the Schema.org initiative specifies a format for the data in terms of so-called items, no information is given on what form of querying is used. We consider conjunctive queries (CQs) and unions of conjunctive queries (UCQ), a basic querying mechanism that is ubiquitous in relational database systems and research, and that also can be viewed as a core of the Semantic Web query language SPARQL. In particular, we also consider CQs and UCQs without quantified variables since these are not allowed in the relevant SPARQL entailment regimes [Glimm and Kr otzsch, 2010]. We often view a pair (O, q) that consists of a schema.org-ontology and an actual query as a compound query called an ontology-mediated query (OMQ). ... We start with the observation that evaluating OMQs is intractable in general, namely Πp 2-complete in combined complexity and CONP-complete in data complexity.
Researcher Affiliation Academia 1University of Liverpool, UK 2University of Bremen, Germany
Pseudocode No The paper describes datalog rules and logical structures, but these are presented within the main text or as mathematical expressions, not as clearly labeled 'Pseudocode' or 'Algorithm' blocks.
Open Source Code No The paper does not provide any links to open-source code for the methodology it describes. It only links to a 'full version' PDF of the paper.
Open Datasets No The paper discusses 'data instances' in a theoretical context (e.g., 'A data instance A is a finite set of concept assertions A(a) where A NC and a NI; role assertions r(a, b) where r NR, a NI and b NI S D DT D'), but it does not mention or provide access to any publicly available dataset used for training or empirical evaluation.
Dataset Splits No The paper does not describe any training, validation, or test dataset splits, as it focuses on theoretical complexity analysis rather than empirical experiments.
Hardware Specification No The paper does not specify any hardware used for experiments. This is a theoretical paper focusing on complexity analysis.
Software Dependencies No The paper discusses description logics and datalog programs as theoretical frameworks, but it does not list any specific software components or libraries with version numbers that would be needed for replication.
Experiment Setup No The paper does not describe any experimental setup details such as hyperparameters or training configurations, as it is a theoretical paper focusing on complexity analysis.