Computer Science
Search Algorithms
Search algorithms are computational procedures used to locate specific items within a collection of data. They are fundamental to information retrieval and are employed in various applications, such as web search engines and database systems. These algorithms are designed to efficiently navigate through large datasets to find the desired information.
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8 Key excerpts on "Search Algorithms"
eBook - PDF- Rex Porbasas Flejoles(Author)
- 2019(Publication Date)
- Arcler Press(Publisher)
Efficient sorting and searching are considered as the fundamental and broadly encountered challenges in the field of computer science. For instance, for a collection of certain objects, the objective of the search algorithm is to find and distinguish a particular object from the others. On the other hand, the search algorithm can perform the identification analysis of a particular object which is not present in the system (Baeza-Yates, 1989; Baeza-Yates et al., 1994). The database objects often possess some key Fundamentals of Search Algorithms 3 values which form the basis for a particular search. Additionally, there are some data values which represent the information intended to be retrieved after an object has been found (Baeza-Yates & Gonnet, 1996; Baeza-Yates & Ribeiro-Neto, 1999). For instance, a telephone book contains a collection of contacts with different names and telephone numbers. The search algorithm is used to locate a particular name or number after incorporation of certain search inputs. It is a common understanding that some data is associated with these key values, i.e., name, number, etc. Let’s consider a search case which involves searching for a single key value (e.g., name). The group of objects is usually stored in an array or a list. Given the collection of n (number of) objects in a particular array A (i.e., A [1... n]), the i th element (i.e., A[i]) typically corresponds to the key value for the i th object present in the collection (Barrow & Burstall, 1976; Barbosa et al., 2001; Boag et al., 2002). The objects are often sorted by using key values (e.g., a phone book), however, this is not essential in all the cases. Different Search Algorithms may be required depending on the sorting condition of the data (i.e., either sorted or not). The inputs for a particular search algorithm include the number of objects (i.e., n), an array of objects (i.e., A) and a key value being required (i.e., x).
eBook - PDFComputing
A Historical and Technical Perspective
- Yoshihide Igarashi, Tom Altman, Mariko Funada, Barbara Kamiyama(Authors)
- 2014(Publication Date)
- Chapman and Hall/CRC(Publisher)
255 C H A P T E R 27 The Design of Computer Algorithms As described in Chapter 18, computers were traditionally built to calculate the solution to numerical problems such as the determination of the roots of an algebraic equation, or to process numerical data, e.g., the statistical calculation of national consensus data. However, for the last 40 years or more, a great deal of important work has also been done by computers for nonnumerical problems, such as sorting, searching, word or language processing, and solving combinatorial problems in software development, data communication, and the simulation of various biological, chemical, and physical processes. The design and analysis of computer algorithms have been developed in the context of such applications. 27.1 SORTING AND SEARCHING Sorting a sequence of numeric or alphanumeric items means rearrang-ing them in some specific order. Since a significant portion of data pro-cessing involves sorting, efficient sorting algorithms are of considerable importance for many practical problems [3, 7]. Sorting is one of the first problems for which algorithms were formally analyzed and evaluated. It is considered to be a fundamental problem in the area of algorithmics , mainly because sorting often plays an essential part of many algorithms. For example, sorting significantly facilitates a search for elements in some set or a list. A dictionary is a typical example of a sorted list. Words in a dictionary are usually arranged in an alphabetical order, which allows us to easily locate the word that we are trying to find in the dictionary. 256 ◾ Computing Some sorting methods were in use long before the invention of computers. For example, a card player sorts the cards of his hand so that each card is visible and individually accessible. Suppose that A , 2, 3, 4, 5, 6, 7, 8, 9, 10, J , Q , K are the order of the cards. The following method has been com-monly used among card players.
eBook - PDF- Yoshio Ohno, Hiroyasu Kakuda, Tsutomu Kamimura(Authors)
- 2014(Publication Date)
- Academic Press(Publisher)
Just as physics has exerted an influence on mathematical concepts, so computer science is today beginning to affect them. This trend is particularly evident in the field of algorithms. In this article, we consider the history of algorithms in society and culture. 1 Formation of the Concept of Algorithm in the History of Math-ematics Loosely speaking, algorithms are procedures for reaching a goal of some kind. How-ever, the range of areas in which algorithms are used, and indeed, the contents and nature of the algorithms themselves, are extremely diverse. Copyright © 1991 by Academic Press, Inc. and 1 7 7 Iwanami Shoten, Publishers. All rights of reproduction in any form reserved. ISBN 0-12-037102-2 178 Advances in Software Science and Technology 2, 1990 Algorithms appear in a variety of contexts: as means of obtaining numerical values or function values, as techniques for judging the truth or falsehood of certain types of proposition, and as methods for winning at certain games. Where numer-ical values are computed, a method of computation — an algorithm — is always involved. It seems useful to distinguish between the discovery and simple execution of the procedure for performing calculations on the one hand, and an awareness of algorithms on the other. By awareness we mean the realization that if opera-tions or manipulations are performed according to the algorithm, the desired result will be obtained. It would seem that such an awareness appeared only long after algorithms themselves. While it is difficult to distinguish clearly between the two, if one could find examples of algorithms devised out of curiosity, not prompted by practical considerations, for studying the behavior of problems and solutions, this would constitute evidence that by that time at the latest, algorithms themselves had become objects of investigation.
eBook - PDF- Xingni Zhou, Qiguang Miao, Lei Feng(Authors)
- 2020(Publication Date)
- De Gruyter(Publisher)
2 Algorithms Main contents – Concept of algorithms – Representation of algorithms – Effectiveness of algorithms – Universality of algorithms – Comprehensiveness of algorithms Learning objectives – Know concepts related to algorithms – Know the characteristics of computer algorithms – Know representations of algorithms – Know general procedures of algorithm design – Can design algorithms in top-down stepwise refinement method Donald Ervin Knuth once said, “ Programs are like blue poems. ” If that is true, then algorithms are the soul of these poems. 2.1 Concept of algorithms 2.1.1 Algorithms in practice Let us take a look at a real-life algorithm: ticket purchasing at the ticket office. When there was no internet, Mr. Brown had to buy train tickets at ticket offices when he needed to take business trips. The main procedures of purchasing tickets are shown in Figure 2.1, in which the key information includes the date, destination, train number, price, and fare. In fact, everything is done under certain conditions and through performing a se-ries of operations. Algorithms are methods and procedures used to solve the problems. Nowadays, Mr. Brown can purchase tickets easily online. The main steps of online pur-chasing are shown in Figure 2.2. Compared with offline purchasing, online purchasing uses the same set of crucial information, except that we are dealing with computer sys-tems instead of a human. Step 1: The passenger provides information on trip date, destination, etc. Step 2: The staff finds trains available on that day Step 3: The passenger chooses a train and determines number of tickets to buy Step 4: The passenger pays the fare and collects tickets Algorithms are methods and procedures used to solve problems. Case Study 1 Purchasing tickets through ticket office Figure 2.1: Flow of purchasing tickets at the ticket office. https://doi.org/10.1515/9783110692327-002
eBook - PDF- Kyla McMullen, Elizabeth Matthews, June Jamrich Parsons, , Kyla McMullen, Kyla McMullen, Elizabeth Matthews, June Jamrich Parsons(Authors)
- 2021(Publication Date)
- Cengage Learning EMEA(Publisher)
PROGRAMMING WITH C++ 426 SUMMARY • To make the large amounts of information that computers store useful to you, a computer needs to effi- ciently search for desired information. Search Algorithms are special algorithms that describe how to find a specific or target piece of information. • The search space defines the amount of data that needs to be examined to find the target. Generally, as the search space increases, the time needed to find the target also increases. • Linear search is the simplest search algorithm. Each element in the search space is examined until the target is located. • Linear search can be performed on any contiguous data structure such as an array or linked list. • In the worst-case scenario, linear search requires you to look at every item in the search space before you find the solution, which is why linear search is rarely used. • A binary search algorithm consecutively divides the search space in half until the target value is located. This approach is typically referred to as a divide-and-conquer technique because each step divides the search space on the path to a solution. • Binary search reduces the search space by half on each iteration. This behavior reduces the number of times you have to evaluate an item to determine if it is equal to your target. If the search space contains n items, binary search takes at most log 2 (n) comparisons to determine the answer. • In a search scenario (such as a search engine), when you have optimized the underlying search algo- rithm, you need a way to specify the information you are seeking. When searching, you can use a regular expression to search for an item, such as a desired contact. A regular expression is a string of characters that describe the pattern of the text for which you are searching. • The characters that describe the patterns used in regular expressions are called metacharacters. You can use metacharacters alone or in combination with other metacharacters to describe patterns.
eBook - PDF- Sourabh Pal(Author)
- 2023(Publication Date)
- Arcler Press(Publisher)
CLASSIFICATION OF ALGORITHMS CHAPTER2 CONTENTS 2.1. Introduction ...................................................................................... 38 2.2. Deterministic and Randomized Algorithms ....................................... 39 2.3. Online Vs. Offline Algorithms ........................................................... 40 2.4. Exact, Approximate, Heuristic, and Operational Algorithms .............. 41 2.5. Classification According to the Main Concept................................... 42 References ............................................................................................... 53 The Fundamentals of Algorithmic Processes 38 2.1. INTRODUCTION An algorithm is a technique or group of methods for completing a problem- solving activity. The term algorithm, which comes from Medieval Latin, refers to more than only computer programming. There are many different sorts of algorithms for various issues. The belief that there are only a finite number of algorithms and that one must learn all of them is a fallacy that leads many potential programers to turn to lawn maintenance as a source of revenue to cover their expenses (Rabin, 1977; Cook, 1983, 1987). When an issue develops throughout the course of developing the complete software, an algorithm is created. A variety of classification schemes for algorithms are discussed in detail in this chapter. There is no single “correct” classification that applies to all situations. When comparing the tasks of classifying algorithms and attributing them, it is important to remember that the former is more difficult (Karp, 1986; Virrer and Simons, 1986). Following a discussion of the labeling procedure for a given algorithm (for example, the divide-and-conquer algorithm), we will examine the various methods for examining algorithms in greater depth.
eBook - PDFAlgorithms: Design Techniques And Analysis
Design Techniques and Analysis
- M H Alsuwaiyel(Author)
- 1999(Publication Date)
- World Scientific(Publisher)
If there is an output for a particular input, then we say that the algorithm can be applied to this input and process it to give the corresponding output. We require that an algorithm halts on every input, which implies that each instruction requires a finite amount of time, and each input has a finite length. We also require that the output of a legal input to be unique, that is, the algorithm is deterministic in the sense that the same set of instructions are executed when the algorithm is initiated on a particular input more than once. In Chapter 14, we will relax this condition when we study randomized algorithms . The design and analysis of algorithms are of fundamental importance in the field of computer science. As Donald E. Knuth stated “Computer science is the study of algorithms”. This should not be surprising, as every area in computer science depends heavily on the design of efficient algo- *According to the American Heritage Dictionary, the word “algorithm” is derived from the name of Muhammad ibn MiisB al-Khwarizrni (780?-850?), a Muslim mathematician whose works introduced Arabic numerals and algebraic concepts to Western rnathemat- ics. The word “algebra” stems from the title of his book Kitab al jabr wa’l-rnuqgbala. 5 6 Basic Concepts in Algorithmic Analysis rithms. As simple examples, compilers and operating systems are nothing but direct implementations of special purpose algorithms. The objective of this chapter is twofold. First, it introduces some simple algorithms, particularly related to searching and sorting. Second, it covers the basic concepts used in the design and analysis of algorithms. We will cover in depth the notion of “running time” of an algorithm, as it is of fundamental importance to the design of efficient algorithms. After all, time is the most precious measure of an algorithm’s efficiency. We will also discuss the other important resource measure, namely the space required by an algorithm.
eBook - PDFEngines of Order
A Mechanology of Algorithmic Techniques
- Bernhard Rieder(Author)
- 2020(Publication Date)
- Amsterdam University Press(Publisher)
If the goal of advanced information retrieval is ‘to make computers do humanlike things’ (Swanson, 1988, p. 97), the invention of algorithmic techniques is its principal vector of progress. Algorithmic Techniques When it comes to making software, programming takes a central place and we can certainly think of it as a cultural technique in the sense of a fundamental skill. Being able to read and write code, to work with constructs such as variables and basic data structures like lists, to arrange control flow via loops and conditional statements, to make use of dif ferent means for inputting and outputting data, and to master related aspects, for example, what it means to execute a program and how to do that, are things not too 6 There is, for example, an open-source project that grew directly out of GroupLens (Resnick et al., 1994), LensKit (http://lenskit.org). 94 ENGINES OF ORDER dissimilar from language prof ic iency or the mastery of basic arithmetic. However, while programming is (mostly) still a fundamental requirement, the much broader practice of making software draws on a wide array of concepts and techniques that cover the already mentioned areas like requirements analysis, process and data modeling, software architecture, interaction design, project management, testing, maintenance, DevOps, 7 and many others. These are by no means minor subjects: the famous ‘software crisis’ of the late 1960s was prompted by the observation that ‘[i]n many sensitive areas, software is late, expensive, unreliable and does not work to specif icat ion’ (Buxton, 1978, p. 23). The emergence of software ‘engineering’ as the ‘systematic, disciplined, quantif iable approach to the development, operation, and maintenance of software’ (IEEE, 1990) was the direct outcome of that crisis.
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