TY - GEN
T1 - Handling Impossible Derivations During Stream Reasoning
AU - Bazoobandi, Hamid R.
AU - Bal, Henri
AU - van Harmelen, Frank
AU - Urbani, Jacopo
PY - 2020
Y1 - 2020
N2 - With the rapid expansion of the Web and the advent of the Internet of Things, there is a growing need to design tools for intelligent analytics and decision making on streams of data. Logic-based frameworks like LARS allow the execution of complex reasoning on such streams, but it is paramount that the computation is completed in a timely manner before the stream expires. To reduce the runtime, we can extend the validity of inferred conclusions to the future to avoid repeated derivations, but this is not enough to avoid all sources of redundant computation. To further alleviate this problem, this paper introduces a new technique that infers the impossibility of certain derivations in the future and blocks the reasoner from performing computation that is doomed to fail anyway. An experimental analysis on microbenchmarks shows that our technique leads to a significant reduction of the reasoning runtime.
AB - With the rapid expansion of the Web and the advent of the Internet of Things, there is a growing need to design tools for intelligent analytics and decision making on streams of data. Logic-based frameworks like LARS allow the execution of complex reasoning on such streams, but it is paramount that the computation is completed in a timely manner before the stream expires. To reduce the runtime, we can extend the validity of inferred conclusions to the future to avoid repeated derivations, but this is not enough to avoid all sources of redundant computation. To further alleviate this problem, this paper introduces a new technique that infers the impossibility of certain derivations in the future and blocks the reasoner from performing computation that is doomed to fail anyway. An experimental analysis on microbenchmarks shows that our technique leads to a significant reduction of the reasoning runtime.
UR - http://www.scopus.com/inward/record.url?scp=85086140085&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086140085&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-49461-2_1
DO - 10.1007/978-3-030-49461-2_1
M3 - Conference contribution
AN - SCOPUS:85086140085
SN - 9783030494605
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 3
EP - 19
BT - The Semantic Web
A2 - Harth, Andreas
A2 - Kirrane, Sabrina
A2 - Ngonga Ngomo, Axel-Cyrille
A2 - Paulheim, Heiko
A2 - Rula, Anisa
A2 - Gentile, Anna Lisa
A2 - Haase, Peter
A2 - Cochez, Michael
PB - Springer
T2 - 17th Extended Semantic Web Conference, ESWC 2020
Y2 - 31 May 2020 through 4 June 2020
ER -
