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About 4,921 papers for “string processing”

String Processing

Advances in systems analysis, software engineering, and high performance computing book series · 2023

In all programming languages, string processing is extremely important. This chapter will present how to declare strings and summarize the commonly used functions of strings, such as indexOf, lastIndexOf, contains, substring, replace, trim, compare, plus, split, upper case and lowercase functions, etc. Each function has sample code along with detailed explanations that make it easy for readers to understand how to use basic string functions. In this chapter, the book will present some of the most commonly used functions in the string. At the end of the chapter there are exercises to help readers improve the skills in string processing.

Cited by 0

String Processing

Edward DongBo Cui · 2024

This chapter examines vectorization operations on string values. NumPy has three data types that can be used to encode string values in its np.ndarray: ‘S’ for byte string; ‘U’ for unicode characters; and ‘O’ or object for encoding objects in general, including strings and bytes. There are several ways to initialize a Pandas column with string data. The chapter also examines how Tensorflow can represent structured data using byte strings. It provides a list of string tensor operations that help vectorize string preprocessing during machine learning tasks. It can be seen that typical string processing tasks in native Python have corresponding operations implemented in Pandas and Tensorflow, thus saving the users from writing for loops when processing a batch of string values. Factorization machine is used as a strong baseline model in building recommendation engines in e-commerce, media streaming, and advertising industries.

Cited by 0Open access

String Processing

James Lee, Simon Cozens, Peter C. Wainwright · Apress eBooks · 2004

Perl was created to be a text processing language, and it is arguably the most powerful text processing language around. One way that Perl displays its power in processing text is through its built-in regular expression support that we discussed in Chapter 7. Perl also has many built-in string operators (such as the string concatenation operator . and the string replication operator x) and string functions. In this chapter we will explore several string functions and one very helpful string operator.

Cited by 0

String Processing

S G Ganesh, Tushar Sharma · Apress eBooks · 2013

String objects are extensively used in writing Java applications. Java programs use strings not only in business logic but also to implement utility functionality such as logging. Therefore, it is useful and important to understand strings and related concepts.

Cited by 0

Approximate String Processing

Marios Hadjieleftheriou, Divesh Srivastava · Foundations and Trends in Databases · 2011

One of the most important primitive data types in modern data processing is text. Text data are known to have a variety of inconsistencies (e.g., spelling mistakes and representational variations). For that reason, there exists a large body of literature related to approximate processing of text. This monograph focuses specifically on the problem of approximate string matching, where, given a set of strings S and a query string υ, the goal is to find all strings s ∈ S that have a user specified degree of similarity to υ. Set S could be, for example, a corpus of documents, a set of web pages, or an attribute of a relational table. The similarity between strings is always defined with respect to a similarity function that is chosen based on the characteristics of the data and application at hand. This work presents a survey of indexing techniques and algorithms specifically designed for approximate string matching. We concentrate on inverted indexes, filtering techniques, and tree data structures that can be used to evaluate a variety of set based and edit based similarity functions. We focus on all-match and top-k flavors of selection and join queries, and discuss the applicability, advantages and disadvantages of each technique for every query type.

Cited by 17

String processing techniques

Stuart Madnick · Communications of the ACM · 1967

The internal organization of string processing systems is discussed. Six techniques for data structures are presented and evaluated on the basis of: (1) creation of strings; (2) examination of strings; and (3) alteration of strings. Speed of operation, storage requirements, effect on paging, and programmer convenience are also considered. One of the techniques, single-word linked blocks, is used in an example demonstrating an implementation of a SNOBOL string processing language on an IBM System/360.

Cited by 21Open access

Quasigroup String Processing

Smile Markovski, Danilo Gligoroski, Verica Bakeva · 1999

Given afi set A we consider quasigroup operations 1 # 2 #:::# n on A and we use them todefi transformations E #D : A ,whereA is the set of allfil strings with members from A.We show that the mappings E and D haveseveral useful properties, suitable for many purposes in cryptography, coding theory, defi and improving (pseudo) random generators, ... . Key words: Markovchain, quasigroup, quasigroup string processing, uniform distribution AMS Mathematics Subject Classification (1991): 20N05, 60J10, 60J20 1 Preliminaries It was noticed in [4] and [5] that quasigroups can be very useful for cryptographic purposes, mainly because there is a huge number of quasigroups operations on a given finite set, and it is easy to define the encoding and decoding functions by using the quasigroup operations as well. In this paper we are treating transformations of the( finite) stings with members of a given finite set A by using quasigroup operations on A,andwe are proving several useful properties of these transformations, confirming the suggestions stated in [4] and [5]. Muchmore, the results that we present here mayhavemany other useful applications. Recall that a Q# ) is a groupoid( i.e. algebra with one binary operation on the set Q) satisfying the law: 8u# v 2 9!x# y 2 x u = v & u y = v)( In fact(c says that the equations x u = v# u y = v for eachgiven u# v 2 Q and x# y unknown, have unique solutions. This implies that any Q# ) allows another quasigroup operation n on Q defined by x n y = z () y = x z(andthenthefollowing equalities are identities in the algebra( Q# # n): x x n y)=y = x x y):( We note that by( 2) the operations and n are mutually defined, i.e. one of these two operations uniquely determines the other one. The usefulness of the q...

Cited by 0

String Processing Algorithms

Shunsuke Inenaga · 2003

The thesis describes extensive studies on various algorithms for efficient string processing. Data available in/via computers are often of enormous size, and thus, it is significantly important and necessary to invent time- and space-efficient methods to process them. Most of such data are, in fact, stored and manipulated as strings. String matching is most fundamental in string processing, where the problem is to examine whether or not a pattern string p occurs in a text string w. There are two cases to consider; p is fixed and w is flexible, and vise versa. In the former case, it is adequate to employ the noble algorithm by Knuth, Morris, and Pratt that solves the problem in O(|w|) time using O(|p|) space. The thesis, on the other hand, considers the latter case. When w is fixed, it is natural, and ideal, to use a data structure that supports indices of w. Such a data structure is called an index structure. A linear-spaced index structure was first given by Weiner in 1973, named suffix trees. Suffix trees are regarded as a compaction of suffix tries that are a basic index structure requiring quadratic space. On the other hand minimizing suffix tries yields another type of index structure called directed

Cited by 0

Distributed EZ (string processing language)

Alvaro E. Campos, David R. Hanson · 2003

EZ is a system that integrates traditional operating systems and programming languages into a very-high-level persistent string processing language. The authors describe the design and initial implementation of a distributed memory manager that distributes EZ's virtual address space transparently among a network of homogeneous computers. The design adapts the techniques used in recent implementation of shared virtual memory for use in EZ's persistent environment. Unlike most implementations of shared virtual memory, control information is distributed and migrates. This memory manager works in concert with a distributed mark-and-sweep garbage collector, which is also concurrent and real-time. This collector trades time for space and minimal disruption of mutators, which reduces communication costs.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 1