Pattern-based analysis of SPARQL queries from the LSQ dataset
In: ISWC 2017 Posters & Demonstrations and Industry Tracks : Proceedings of the ISWC 2017 Posters & Demonstrations and Industry Tracks / Nikitina, Nadeschda; Song, Dezhao (Hrsg.). - Posters & Demonstrations and Industry Tracks at the International Semantic Web Conference (ISWC 2017), 23-25 October 2017, Vienna, Austria - Aachen: RWTH Aachen, 2017 - (CEUR Workshop Proceedings ; 1963)
2017Buchaufsatz/Kapitel in TagungsbandOA Gold
InformatikFakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft
Titel in Englisch:
Pattern-based analysis of SPARQL queries from the LSQ dataset
Autor*in:
Stegemann, TimoUDE
- LSF ID
- 53437
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
- GND
- 1015876811
- LSF ID
- 3881
- ORCID
-
0000-0001-9603-5272
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
Open Access?:
OA Gold
Scopus ID
Notiz:
OA platinum
Sprache des Textes:
Englisch
Erschienen in
ISWC 2017 Posters & Demonstrations and Industry Tracks : Proceedings of the ISWC 2017 Posters & Demonstrations and Industry Tracks
Konferenz
Posters & Demonstrations and Industry Tracks at the International Semantic Web Conference (ISWC 2017), 23-25 October 2017, Vienna, Austria
Herausgeber*in:
Nikitina, Nadeschda;Song, Dezhao
Erscheinungsort:
Aachen
Verlag:
RWTH Aachen
Erscheinungsjahr:
2017
ISSN
ZDB ID
Ressourcentyp:
Text
Abstract:
This paper presents a pattern-based analysis of the Linked Sparql Queries dataset (Lsq). The analysis showed that from more than 630,000 unique Select queries stored in the dataset, 99% of them are represented by only 120 different query patterns.