Topic
String (computer science)
About: String (computer science) is a research topic. Over the lifetime, 19430 publications have been published within this topic receiving 333247 citations. The topic is also known as: str & s.
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TL;DR: In this paper, similarity measure based on 2D string longest common subsequence is defined and the algorithm for similarity retrieval is also proposed.
141 citations
Patent•
08 Dec 1989TL;DR: A data compression system in which a dictionary stored strings of characters and an encoder matched the longest of the stored string with a current string of a data stream input to the encoder is described in this paper.
Abstract: A data compression system in which a dictionary stored strings of characters and an encoder matches the longest of the stored string with a current string of a data stream input to the encoder. The index of the longest matched stored string is output by the encoder and the dictionary is updated by a new string consisting of the previous match concatenated with the first two characters only of the present match. If the present match has only one or two characters, it is added without reduction.
140 citations
01 Dec 1993
TL;DR: This document defines a human-readable string format for representing LDAP search filters, a network representation of a search filter transmitted to an LDAP server.
Abstract: The Lightweight Directory Access Protocol (LDAP) [1] defines a network representation of a search filter transmitted to an LDAP server. Some applications may find it useful to have a common way of representing these search filters in a human-readable form. This document defines a human-readable string format for representing LDAP search filters.
140 citations
TL;DR: A stacking model by combining GBDT, XGBoost and LightGBM in multiple layers is devised, which enables different models to be complementary, thus improving the performance on phishing webpage detection.
139 citations
TL;DR: This work describes several approximation algorithms that produce solutions that are always within a factor of two of optimum with respect to the overlap measure of the shortest common superstring problem (SCS).
Abstract: The object of the shortest common superstring problem (SCS) is to find the shortest possible string that contains every string in a given set as substrings. As the problem is NP-complete, approximation algorithms are of interest. The value of an aproximate solution to SCS is normally taken to be its length, and we seek algorithms that make the length as small as possible. A different measure is given by the sum of the overlaps between consecutive strings in a candidate solution. When considering this measure, the object is to find solutions that make it as large as possible. These two measures offer different ways of viewing the problem. While the two viewpoints are equivalent with respect to optimal solutions, they differ with respect to approximate solutions. We describe several approximation algorithms that produce solutions that are always within a factor of two of optimum with respect to the overlap measure. We also describe an efficient implementation of one of these, using McCreight's compact suffix tree construction algorithm. The worstcase running time is O ( m log n ) for small alphabets, where m is the sum of the lengths of all the strings in the set and n is the number of strings. For large alphabets, the algorithm can be implemented in O ( m log m ) time by using Sleator and Tarjan's lexicographic splay tree data structure.
139 citations