TY - GEN
T1 - Õ(n+poly(k))-time Algorithm for Bounded Tree Edit Distance
AU - Das, Debarati
AU - Gilbert, Jacob
AU - Hajiaghayi, Mohammad Taghi
AU - Kociumaka, Tomasz
AU - Saha, Barna
AU - Saleh, Hamed
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Computing the edit distance of two strings is one of the most basic problems in computer science and combinatorial optimization. Tree edit distance is a natural generalization of edit distance in which the task is to compute a measure of dissimilarity between two (unweighted) rooted trees with node labels. Perhaps the most notable recent application of tree edit distance is in NoSQL big databases, such as MongoDB, where each row of the database is a JSON document represented as a labeled rooted tree and finding dissimilarity between two rows is a basic operation. Until recently, the fastest algorithm for tree edit distance ran in cubic time (Demaine, Mozes, Rossman, Weimann; TALG'10); however, Mao (FOCS'21) broke the cubic barrier for the tree edit distance problem using fast matrix multiplication.Given a parameter k as an upper bound on the distance, an O(n+k2)-time algorithm for edit distance has been known since the 1980s due to works of Myers (Algorithmica'86) and Landau and Vishkin (JCSS'88). The existence of an O(n+poly(k))-time algorithm for tree edit distance has been posed as open question, e.g., by Akmal and Jin (ICALP'21), who give a stateof-the-art O(nk2)-time algorithm. In this paper, we answer this question positively.
AB - Computing the edit distance of two strings is one of the most basic problems in computer science and combinatorial optimization. Tree edit distance is a natural generalization of edit distance in which the task is to compute a measure of dissimilarity between two (unweighted) rooted trees with node labels. Perhaps the most notable recent application of tree edit distance is in NoSQL big databases, such as MongoDB, where each row of the database is a JSON document represented as a labeled rooted tree and finding dissimilarity between two rows is a basic operation. Until recently, the fastest algorithm for tree edit distance ran in cubic time (Demaine, Mozes, Rossman, Weimann; TALG'10); however, Mao (FOCS'21) broke the cubic barrier for the tree edit distance problem using fast matrix multiplication.Given a parameter k as an upper bound on the distance, an O(n+k2)-time algorithm for edit distance has been known since the 1980s due to works of Myers (Algorithmica'86) and Landau and Vishkin (JCSS'88). The existence of an O(n+poly(k))-time algorithm for tree edit distance has been posed as open question, e.g., by Akmal and Jin (ICALP'21), who give a stateof-the-art O(nk2)-time algorithm. In this paper, we answer this question positively.
UR - http://www.scopus.com/inward/record.url?scp=85146356649&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146356649&partnerID=8YFLogxK
U2 - 10.1109/FOCS54457.2022.00071
DO - 10.1109/FOCS54457.2022.00071
M3 - Conference contribution
AN - SCOPUS:85146356649
T3 - Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
SP - 686
EP - 697
BT - Proceedings - 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science, FOCS 2022
PB - IEEE Computer Society
T2 - 63rd IEEE Annual Symposium on Foundations of Computer Science, FOCS 2022
Y2 - 31 October 2022 through 3 November 2022
ER -