@Article{TextSearchLB_JAlgorithms,
AUTHOR = {Erik D. Demaine and Alejandro L\'opez-Ortiz},
TITLE = {A Linear Lower Bound on Index Size for Text Retrieval},
JOURNAL = {Journal of Algorithms},
JOURNALURL = {http://www.elsevier.com/locate/jalgor},
VOLUME = 48,
NUMBER = 1,
MONTH = {August},
YEAR = 2003,
PAGES = {2--15},
NOTE = {Special issue of selected papers from the 12th Annual
ACM-SIAM Symposium on Discrete Algorithms, 2001.},
papers = {SODA2001b},
replaces = {SODA2001b},
length = {14 pages},
doi = {https://dx.doi.org/10.1016/S0196-6774(03)00043-9},
dblp = {https://dblp.org/rec/journals/jal/DemaineL03},
comments = {This paper is also available from the
<A HREF="http://dx.doi.org/10.1016/S0196-6774(03)00043-9">ScienceDirect</A>.},
}
In this work we prove a linear worst-case lower bound on the size of any index that reports the location (if any) of a substring in the text in time proportional to the length of the pattern. In other words, an index supporting linear-time substring searches requires about as much space as the original text. Here “time” is measured in the number of bit probes to the text; an arbitrary amount of computation may be done on an arbitrary amount of the index. Our lower bound applies to inverted word indices as well.