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      <title>SPIRE2000-Hirao</title>
      <link>https://www.iss.is.tohoku.ac.jp/publications/2000-09-spire2000-hirao/</link>
      <pubDate>Wed, 27 Sep 2000 00:00:00 +0000</pubDate>
      <guid>https://www.iss.is.tohoku.ac.jp/publications/2000-09-spire2000-hirao/</guid>
      <description>&lt;p&gt;Internal Pattern Matching (IPM) queries on a text $T$, given two fragments $X$ and $Y$ of $T$ such that $|Y|&amp;lt;2|X|$, ask to compute all exact occurrences of $X$ within $Y$. IPM queries have been introduced by Kociumaka, Radoszewski, Rytter, and Wale&#39;n [SODA&#39;15&amp;amp;SICOMP&#39;24], who showed that they can be answered in $O(1)$ time using a data structure of size $O(n)$ and used this result to answer various queries about fragments of $T$. In this work, we study IPM queries on compressed and dynamic strings. Our result is an $O(\log n)$-time query algorithm applicable to any balanced recompression-based run-length straight-line program (RLSLP). In particular, one can use it on top of the RLSLP of Kociumaka, Navarro, and Prezza [IEEE TIT&#39;23], whose size $O\big(\delta \log \frac{n\log \sigma}{\delta \log n}\big)$ is optimal (among all text representations) as a function of the text length $n$, the alphabet size $\sigma$, and the substring complexity $\delta$. Our procedure does not rely on any preprocessing of the underlying RLSLP, which makes it readily applicable on top of the dynamic strings data structure of Gawrychowski, Karczmarz, Kociumaka, {\L}\k{a}cki and Sankowski [SODA&#39;18], which supports fully persistent updates in logarithmic time with high probability.&lt;/p&gt;</description>
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      <title>SPIRE2000-Hoshino</title>
      <link>https://www.iss.is.tohoku.ac.jp/publications/2000-09-spire2000-hoshino/</link>
      <pubDate>Wed, 27 Sep 2000 00:00:00 +0000</pubDate>
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      <description>&lt;p&gt;We consider a deterministic finite automaton which accepts all subsequences of a set of texts, called subsequence automaton. We show an online algorithm for constructing a subsequence automaton for a set of texts. It runs in O(|/spl Sigma/|(m+k)+N) time using O(|/spl Sigma/|m) space, where |/spl Sigma/| is the size of alphabet, m is the size of the resulting subsequence automaton, k is the number of texts, and N is the total length of texts. It can be used to preprocess a given set S of texts in such a way that for any query /spl omega/ /spl isin/ /spl Sigma/*, returns in O(|/spl omega/|) time the number of texts in S which contain /spl omega/ as a subsequence. We also show an upper bound of the size of automaton compared to the minimum automaton.&lt;/p&gt;</description>
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