Demo Data from EDBT 2026 / reviewers in the wild / expert
Julio Lemos
dblp:139/1028
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Computational complexity · 100% | |
| Artificial intelligence
1 paper |
Knowledge representation and reasoning · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology |
0.3 | 1 | 2017 | Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach · AAAI 2017 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology-based query answering |
0.3 | 1 | 2017 | Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach · AAAI 2017 |
Computational complexity › complexity of reasoning
data complexity |
0.3 | 1 | 2017 | Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach · AAAI 2017 |
Computational complexity › constraint satisfaction › dichotomy theorem
dichotomy classification |
0.3 | 1 | 2017 | Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach · AAAI 2017 |
Computational complexity
constraint satisfaction |
0.1 | 1 | 2017 | Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach · AAAI 2017 |
Computational complexity › constraint satisfaction › infinite-domain constraint satisfaction
temporal constraint satisfaction |
0.1 | 1 | 2017 | Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach · AAAI 2017 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Query Answering in DL-Lite with Datatypes: A Non-Uniform ApproachabstractAdding datatypes to ontology-mediated queries (OMQs) often makes query answering hard. As a consequence, the use of datatypes in OWL 2 QL has been severely restricted. In this paper we propose a new, non-uniform, way of analyzing the data-complexity of OMQ answering with datatypes. Instead of restricting the ontology language we aim at a classification of the patterns of datatype atoms in OMQs into those that can occur in non-tractable OMQs and those that only occur in tractable OMQs. To this end we establish a close link between OMQ answering with datatypes and constraint satisfaction problems over the datatypes. In a case study we apply this link to prove a P/coNP-dichotomy for OMQs over DL-Lite extended with the datatype (Q,<=). The proof employs a recent dichotomy result by Bodirsky and Kára for temporal constraint satisfaction problems. André Hernich, Julio Lemos, Frank Wolter |
AAAI | 2 |