An edited volume containing data structures and algorithms for information retrieved including a disk with examples written in C. For programmers and students interested in parsing text, automated indexing, its the first collection in book form of the basic data structures and algorithms that are critical to the storage and retrieval of documents.

https://hornad.fei.tuke.sk/~genci/Vyucba/OOBDS/Archiv/Podklady/TExtoveIS&IR/Information%20Retrieval%20Data%20Structures%20&%20Algorithms.PDF

Information Retrieval: Data Structures and Algorithms

Publisher Summary This chapter discusses the algorithms for solving string-matching problems that have proven useful for text-editing and text-processing applications. String pattern matching is an important problem that occurs in many areas of science and information processing. In computing, it occurs naturally as part of data processing, text editing, term rewriting, lexical analysis, and information retrieval. Many text editors and programming languages have facilities for matching strings. In biology, string-matching problems arise in the analysis of nucleic acids and protein sequences, and in the investigation of molecular phylogeny. String matching is also one of the central and most widely studied problems in theoretical computer science. The simplest form of the problem is to locate an occurrence of a keyword as a substring in a sequence of characters, which is called the input string. For example, the input string queueing contains the keyword ueuei as a substring. Even for this problem, several innovative, theoretically interesting algorithms have been devised that run significantly faster than the obvious brute-force method.

Algorithms for finding patterns in strings

We present experimental results for string matching algorithms which are known to be fast in practice. We compare these algorithms through two aspects : the number of text character inspections and the running time. These experiments show that for large alphabets and small patterns the Quick Search algorithm of Sunday is the most efficient and that for small alphabets and large patterns it is the Reverse Factor algorithm of Crochemore et al. which is the most efficient.

Experimental results on string matching algorithms

By reducing an array matching problem to a string matching problem in a natural way, it is shown that efficient string matching algorithms can be applied to arrays, assuming that a linear preprocessing is made on the text.

A technique for two-dimensional pattern matching

In this paper we present a short survey and experimental results for well known sequential string matching algorithms. We consider algorithms based on different approaches including classical, suffix automata, bit-parallelism and hashing. We put special emphasis on algorithms recently presented such as Shift-Or and BNDM algorithms. We compare these algorithms in terms of the number of character comparisons and the running time for four different types of text: binary alphabet, alphabet of size 8, English alphabet and DNA alphabet.

On-line string matching algorithms: survey and experimental results

This paper describes four algorithms of varying complexity used for pattern matching, and investigates their behaviour. The algorithms are tested using patterns of varying length from several alphabets. It is concluded that although there is no overall ‘best’ algorithm, the more complex algorithms are worth considering as they are generally more efficient in terms of number of comparisons made and execution time.

G Davies

Papers

Algorithms for pattern matching