TY - GEN
T1 - Dynamic set intersection
AU - Kopelowitz, Tsvi
AU - Pettie, Seth
AU - Porat, Ely
N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Consider the problem of maintaining a family F of dynamic sets subject to insertions, deletions, and set-intersection reporting queries: given S, S′ ∈ F, report every member of S ∩S′ in any order. We show that in the word RAM model, where w is the word size, given a cap d on the maximum size of any set, we can support set intersection queries in O(Equation found) expected time, and updates in O(1) expected time. Using this algorithm we can list all t triangles of a graph G = (V, E) in O(Equation found) expected time, where m = |E| and α is the arboricity of G. This improves a 30-year old triangle enumeration algorithm of Chiba and Nishizeki running in O(mα) time. We provide an incremental data structure on F that supports intersection witness queries, where we only need to find one e ∈ S ∩ S′. Both queries and insertions take O (Equation found) expected time, where N = ΣS ∈F |S|. Finally, we provide time/space tradeoffs for the fully dynamic set intersection reporting problem. Using M words of space, each update costs O(√M logN) expected time, each reporting query costs O(Equation found) expected time where op is the size of the output, and each witness query costs O(Equation found) expected time.
AB - Consider the problem of maintaining a family F of dynamic sets subject to insertions, deletions, and set-intersection reporting queries: given S, S′ ∈ F, report every member of S ∩S′ in any order. We show that in the word RAM model, where w is the word size, given a cap d on the maximum size of any set, we can support set intersection queries in O(Equation found) expected time, and updates in O(1) expected time. Using this algorithm we can list all t triangles of a graph G = (V, E) in O(Equation found) expected time, where m = |E| and α is the arboricity of G. This improves a 30-year old triangle enumeration algorithm of Chiba and Nishizeki running in O(mα) time. We provide an incremental data structure on F that supports intersection witness queries, where we only need to find one e ∈ S ∩ S′. Both queries and insertions take O (Equation found) expected time, where N = ΣS ∈F |S|. Finally, we provide time/space tradeoffs for the fully dynamic set intersection reporting problem. Using M words of space, each update costs O(√M logN) expected time, each reporting query costs O(Equation found) expected time where op is the size of the output, and each witness query costs O(Equation found) expected time.
UR - http://www.scopus.com/inward/record.url?scp=84951846629&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-319-21840-3_39
DO - https://doi.org/10.1007/978-3-319-21840-3_39
M3 - منشور من مؤتمر
SN - 9783319218397
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 470
EP - 481
BT - Algorithms and Data Structures - 14th International Symposium, WADS 2015, Proceedings
A2 - Dehne, Frank
A2 - Sack, Jorg-Rudiger
A2 - Stege, Ulrike
PB - Springer Verlag
T2 - 14th International Symposium on Algorithms and Data Structures, WADS 2015
Y2 - 5 August 2015 through 7 August 2015
ER -