Often you encounter the problems that involve string processing and file input and output. Suppose you need to write a program to replace all occurrences of a word with a new word in a file. How do you solve this problem? This chapter introduces strings and text files, which will enable you to solve this problem.
A character-based measure of similarity is an important component of many natural language processing systems, including approaches to transliteration, coreference, word alignment, spelling correction, and the identiﬁcation of cognates in related vocabularies. We propose an alignment-based discriminative framework for string similarity. We gather features from substring pairs consistent with a character-based alignment of the two strings.
The limited capacity of working memory is intrinsic to human sentence processing, and therefore must be addressed by any theory of human sentence processing. This paper gives a theory of garden-path effects and processing overload that is based on simple assumptions about human short term memory capacity. hypothesis, is easily compatible with the above view of processing load calculation: given a choice between two different representations for the same input string, simply choose the representation that is associated with the lower processing load. ...
String transformation systems have been introduced in (Brill, 1995) and have several applications in natural language processing. In this work we consider the computational problem of automatically learning from a given corpus the set of transformations presenting the best evidence. We introduce an original data structure and efficient algorithms that learn some families of transformations that are relevant for part-of-speech tagging and phonological rule systems.
Learning for sentence re-writing is a fundamental task in natural language processing and information retrieval. In this paper, we propose a new class of kernel functions, referred to as string re-writing kernel, to address the problem. A string re-writing kernel measures the similarity between two pairs of strings, each pair representing re-writing of a string. It can capture the lexical and structural similarity between two pairs of sentences without the need of constructing syntactic trees.
We have analyzed definitions from Webster's Seventh New Collegiate Dictionary using Sager's Linguistic String Parser and again using basic UNIX text processing utilities such as grep and awk. Tiffs paper evaluates both procedures, compares their results, and discusses possible future lines of research exploiting and combining their respective strengths. Introduction As natural language systems grow more sophisticated, they need larger and more d ~ l e d lexicons.
Chapter 8: String and Tries studies basic combinatorial properties of strings, sequences of characters or letters drawn from a fixed alphabet, and introduces algorithms that process strings ranging from fundamental methods at the heart of the theory of computation to practical text-processing methods with a host of important applications.
Chapter 9 - Characters and strings. After you have read and studied this chapter, you should be able to: Declare and manipulate data of the char data type; write string processing program, applicable in areas such as bioinformatics, using String, StringBuilder, and StringBuffer objects; differentiate the three string classes and use the correct class for a given task; specify regular expressions for searching a pattern in a string; use the Pattern and Matcher classes; compare the String objects correctly.
After completing this unit, you should be able to: Learn about arrays, explore how to declare and manipulate data into arrays, understand the meaning of “array index out of bounds”, become familiar with the restrictions on array processing, discover how to pass an array as a parameter to a function,…
Introduction to java programming: Chapter 8 - Strings and Text I/O's Objectives is to use the String class to process fixed strings; use the Character class to process a single character; use the StringBuilder/StringBuffer class to process flexible strings.
This book is to examine the most important algorithms in use on
today's computers and to teach the basic techniques with the increasing number
who was interested in computer users becoming increasingly serious. It is appropriate
for use as a textbook for a course Monday, Tuesday or Wednesday in the computer
Science: After students have had some programming skills and familiarity
computer system, but before they have advanced specialized courses
field of computer science or computer applications.
contains the information you need to get started
with the Laboratory Virtual Instrument Engineering Workbench
(LabVIEW) software package. LabVIEW simplifies scientific
computation, process control, and test and measurement applications,
and you can also use it for a wide variety of other programming
This manual gives you an overview of the fundamental concepts of
LabVIEW, and includes lessons to teach you what you need to know to
build your own virtual instruments (VIs) as quickly as possible. This
manual does not explain every LabVIEW feature.
Functions of Drilling Fluids
A drilling ﬂuid, or mud, is any ﬂuid that is used in a drilling operation in which that ﬂuid is circulated or pumped from the surface, down the drill string, through the bit, and back to the surface via the annulus. Drilling ﬂuids satisfy many needs in their capacity to do the following [M-I llc]:
. Suspend cuttings (drilled solids), remove them from the bottom of the . . . . . . .
Từ "algorism" và sau này trở thành "algorithm" được giải thích trong từ điển Webster đó như sau:
là Nghệ thuật tính toán bởi chín chữ số và số không hoặc Tập hợp các qui tắc và thủ tục theo trật tự nhất định để giải quyết một vấn đề. Trở lại quá khứ xa hơn trong từ điển toán học Vollstandiges Mathematiesches Lexikon, Leipzig, 1747 có giải thích rằng algorithm là "tổ hợp của bốn phép toán số học bao gồm cộng, trừ, nhân, chia".