374 research outputs found
大腸がんに対するレゴラフェニブの標準開始用量と減量開始用量に関する比較:過去起点コホート研究
京都大学新制・課程博士博士(医学)甲第23067号医博第4694号新制||医||1049(附属図書館)京都大学大学院医学研究科医学専攻(主査)教授 今中 雄一, 教授 武藤 学, 教授 妹尾 浩学位規則第4条第1項該当Doctor of Medical ScienceKyoto UniversityDFA
c-trie++: A Dynamic Trie Tailored for Fast Prefix Searches
Given a dynamic set of strings of total length whose characters
are drawn from an alphabet of size , a keyword dictionary is a data
structure built on that provides locate, prefix search, and update
operations on . Under the assumption that
characters fit into a single machine word , we propose a keyword dictionary
that represents in bits of space,
supporting all operations in expected time on an
input string of length in the word RAM model. This data structure is
underlined with an exhaustive practical evaluation, highlighting the practical
usefulness of the proposed data structure, especially for prefix searches - one
of the most elementary keyword dictionary operations
An Improved Data Structure for Left-Right Maximal Generic Words Problem
For a set D of documents and a positive integer d, a string w is said to be d-left-right maximal, if (1) w occurs in at least d documents in D, and (2) any proper superstring of w occurs in less than d documents. The left-right-maximal generic words problem is, given a set D of documents, to preprocess D so that for any string p and for any positive integer d, all the superstrings of p that are d-left-right maximal can be answered quickly. In this paper, we present an O(n log m) space data structure (in words) which answers queries in O(|p| + o log log m) time, where n is the total length of documents in D, m is the number of documents in D and o is the number of outputs. Our solution improves the previous one by Nishimoto et al. (PSC 2015), which uses an O(n log n) space data structure answering queries in O(|p|+ r * log n + o * log^2 n) time, where r is the number of right-extensions q of p occurring in at least d documents such that any proper right extension of q occurs in less than d documents
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