Years and Authors of Summarized Original Work
2005; Ferragina, Luccio, Manzini, Muthukrishnan
Problem Definition
Trees are a fundamental structure in computing. They are used in almost every aspect of modeling and representation for computations like searching for keys, maintaining directories, and representations of parsing or execution traces, to name just a few. One of the latest uses of trees is XML, the de facto format for data storage, integration, and exchange over the Internet (see http://www.w3.org/XML/). Explicit storage of trees, with one pointer per child as well as other auxiliary information (e.g., label), is often taken as given but can account for the dominant storage cost. Just to have an idea, a simple tree encoding needs at least 16 bytes per tree node: one pointer to the auxiliary information (e.g., node label) plus three node pointers to the parent, the first child, and the next sibling. This large space occupancy may even prevent the processing of medium-sized...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Barbay J, Golynski A, Munro JI, Rao SS (2007) Adaptive searching in succinctly encoded binary relations and tree-structured documents. Theor Comput Sci 387:284–297
Barbay J, He M, Munro JI, Rao SS (2011) Succinct indexes for strings, binary relations and multi-labeled trees. ACM Trans Algorithms 7(4):article 52
Benoit D, Demaine E, Munro JI, Raman R, Raman V, Rao SS (2005) Representing trees of higher degree. Algorithmica 43:275–292
Burrows M, Wheeler D (1994) A block sorting lossless data compression algorithm. Technical report 124, Digital Equipment Corporation
Farzan A, Munro JI (2014) A uniform paradigm to succinctly encode various families of trees. Algorithmica 68(1):16–40
Farzan A, Raman R, Rao SS (2009) Universal succinct representations of trees? In: Proceedings of the 36th international colloquium on automata, languages and programming (ICALP, Part I), Rhodes. Lecture notes in computer science, vol 5555. Springer, pp 451–462
Ferragina P, Venturini R (2007) A simple storage scheme for strings achieving entropy bounds. Theor Comput Sci 372(1):115–121
Ferragina P, Luccio F, Manzini G, Muthukrishnan S (2005) Structuring labeled trees for optimal succinctness, and beyond. In: Proceedings of the 46th IEEE symposium on foundations of computer science (FOCS), Cambridge, pp 184–193. The journal version of this paper appear in J ACM 57(1) (2009)
Ferragina P, Luccio F, Manzini G, Muthukrishnan S (2006) Compressing and searching XML data via two zips. In: Proceedings of the 15th World Wide Web conference (WWW), Edingburg, pp 751–760
Geary R, Raman R, Raman V (2006) Succinct ordinal trees with level-ancestor queries. ACM Trans Algorithms 2:510–534
He M, Munro JI, Rao SS (2012) Succinct ordinal trees based on tree covering. ACM Trans Algorithms 8(4):article 42
He M, Munro JI, Zhou G (2012) A framework for succinct labeled ordinal trees over large alphabets. In: Proceedings of the 23rd international symposium on algorithms and computation (ISAAC), Taipei. Lecture notes in computer science, vol 7676. Springer, pp 537–547
Jacobson G (1989) Space-efficient static trees and graphs. In: Proceedings of the 30th IEEE symposium on foundations of computer science (FOCS), Triangle Park, pp 549–554
Jansson J, Sadakane K, Sung W Ultra-succinct representation of ordered trees. J Comput Syst Sci 78: 619–631 (2012)
Kosaraju SR (1989) Efficient tree pattern matching. In: Proceedings of the 20th IEEE foundations of computer science (FOCS), Triangle Park, pp 178–183
Munro JI, Raman V (2001) Succinct representation of balanced parentheses and static trees. SIAM J Comput 31(3):762–776
Navarro G, Mäkinen V (2007) Compressed full text indexes. ACM Comput Surv 39(1):article 2
Navarro G, Sadakane K (2014) Fully functional static and dynamic succinct trees. ACM Trans Algorithms 10(3):article 16
Raman R, Raman V, Rao SS (2007) Succinct indexable dictionaries with applications to encoding k-ary trees and multisets. ACM Trans Algorithms 3(4):article 43
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this entry
Cite this entry
Satti, P.F.R. (2016). Compressing and Indexing Structured Text. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_430
Download citation
DOI: https://doi.org/10.1007/978-1-4939-2864-4_430
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-2863-7
Online ISBN: 978-1-4939-2864-4
eBook Packages: Computer ScienceReference Module Computer Science and Engineering