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String Metrics
In mathematics and computer science, a string metric (also known as a string similarity metric or string distance function) is a metric that measures distance ("inverse similarity") between two text strings for approximate string matching or comparison and in fuzzy string searching. A requirement for a string ''metric'' (e.g. in contrast to string matching) is fulfillment of the triangle inequality. For example, the strings "Sam" and "Samuel" can be considered to be close. A string metric provides a number indicating an algorithm-specific indication of distance. The most widely known string metric is a rudimentary one called the Levenshtein distance (also known as edit distance). It operates between two input strings, returning a number equivalent to the number of substitutions and deletions needed in order to transform one input string into another. Simplistic string metrics such as Levenshtein distance have expanded to include phonetic, token, grammatical and character-based ...
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Mathematics
Mathematics is a field of study that discovers and organizes methods, Mathematical theory, theories and theorems that are developed and Mathematical proof, proved for the needs of empirical sciences and mathematics itself. There are many areas of mathematics, which include number theory (the study of numbers), algebra (the study of formulas and related structures), geometry (the study of shapes and spaces that contain them), Mathematical analysis, analysis (the study of continuous changes), and set theory (presently used as a foundation for all mathematics). Mathematics involves the description and manipulation of mathematical object, abstract objects that consist of either abstraction (mathematics), abstractions from nature orin modern mathematicspurely abstract entities that are stipulated to have certain properties, called axioms. Mathematics uses pure reason to proof (mathematics), prove properties of objects, a ''proof'' consisting of a succession of applications of in ...
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Machine Learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ...
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L1 Distance
Taxicab geometry or Manhattan geometry is geometry where the familiar Euclidean distance is ignored, and the distance between two points is instead defined to be the sum of the absolute differences of their respective Cartesian coordinates, a distance function (or metric) called the ''taxicab distance'', ''Manhattan distance'', or ''city block distance''. The name refers to the island of Manhattan, or generically any planned city with a rectangular grid of streets, in which a taxicab can only travel along grid directions. In taxicab geometry, the distance between any two points equals the length of their shortest grid path. This different definition of distance also leads to a different definition of the length of a curve, for which a line segment between any two points has the same length as a grid path between those points rather than its Euclidean length. The taxicab distance is also sometimes known as ''rectilinear distance'' or distance (see ''Lp'' space). This geometry ha ...
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Damerau–Levenshtein Distance
In information theory and computer science, the Damerau–Levenshtein distance (named after Frederick J. Damerau and Vladimir I. Levenshtein.) is a string metric for measuring the edit distance between two sequences. Informally, the Damerau–Levenshtein distance between two words is the minimum number of operations (consisting of insertions, deletions or substitutions of a single character, or transposition of two adjacent characters) required to change one word into the other. The Damerau–Levenshtein distance differs from the classical Levenshtein distance by including transpositions among its allowable operations in addition to the three classical single-character edit operations (insertions, deletions and substitutions). In his seminal paper, Damerau stated that in an investigation of spelling errors for an information-retrieval system, more than 80% were a result of a single error of one of the four types. Damerau's paper considered only misspellings that could be correc ...
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Edit Distance
In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two String (computing), strings (e.g., words) are to one another, that is measured by counting the minimum number of operations required to transform one string into the other. Edit distances find applications in natural language processing, where automatic Spell checker, spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question. In bioinformatics, it can be used to quantify the similarity of DNA sequences, which can be viewed as strings of the letters A, C, G and T. Different definitions of an edit distance use different sets of like operations. Levenshtein distance operations are the removal, insertion, or substitution of a character in the string. Being the most common metric, the term ''Levenshtein distance'' is often used interchangeably with ''edit ...
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Knowledge Integration
Knowledge integration is the process of synthesizing multiple knowledge models (or representations) into a common model (representation). Compared to information integration, which involves merging information having different schemas and representation models, knowledge integration focuses more on synthesizing the understanding of a given subject from different perspectives. For example, multiple interpretations are possible of a set of student grades, typically each from a certain perspective. An overall, integrated view and understanding of this information can be achieved if these interpretations can be put under a common model, say, a student performance index. ThWeb-based Inquiry Science Environment (WISE) from the University of California at Berkeley has been developed along the lines of knowledge integration theory. Knowledge integration has also been studied as the process of incorporating new information into a body of existing knowledge with an interdisciplinary appro ...
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Shlomi Dolev
Shlomi Dolev (; born December 5, 1958) is a Rita Altura Trust Chair Professor in Computer Science at Ben-Gurion University of the Negev (BGU) and the head of the BGU Negev Hi-Tech Faculty Startup Accelerato Biography Shlomi Dolev received Bachelor of Science, B.Sc. in Civil Engineering in 1984, B.A. in Computer Science in 1985, and his M.Sc. and D.Sc. in computer science in 1990 and 1992 respectively from the Technion Israel Institute of Technology. From 1992 to 1995, he was at Texas A&M University as a visiting research specialist. Academic career In 1995 Dolev joined the Department of Mathematics and Computer Science at BGU. He was the founder and first department head of the Computer Science Department, established in 2000. After 15 years, the department was ranked among the first 150 best departments in the world. He is the author of Self-Stabilization published by MIT Press in 2000. From 2011 to 2014, Dolev served as Dean of the Natural Sciences Faculty. From 2010 he has ...
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Malware
Malware (a portmanteau of ''malicious software'')Tahir, R. (2018)A study on malware and malware detection techniques . ''International Journal of Education and Management Engineering'', ''8''(2), 20. is any software intentionally designed to cause disruption to a computer, server (computing), server, Client (computing), client, or computer network, leak private information, gain unauthorized access to information or systems, deprive access to information, or which unknowingly interferes with the user's computer security and privacy. Researchers tend to classify malware into one or more sub-types (i.e. computer viruses, Computer worm, worms, Trojan horse (computing), Trojan horses, logic bombs, ransomware, spyware, adware, rogue software, Wiper (malware), wipers and keyloggers). Malware poses serious problems to individuals and businesses on the Internet. According to NortonLifeLock, Symantec's 2018 Internet Security Threat Report (ISTR), malware variants number has increased to 66 ...
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Data Integration
Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories). The decision to integrate data tends to arise when the volume, complexity (that is, big data) and need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Data integration encourages collaboration between internal as well as external users. The data being integrated must be received from a heterogeneous database system and transformed to a single coherent data store that provides synchronous data across a network of files for clients. A common use of data integration is in data mining when analyzing and extracting information from exist ...
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Incremental Search
In computing, incremental search, also known as hot search, incremental find or real-time suggestions, is a user interface interaction method to progressively search for and filter through text. As the user types text, one or more possible matches for the text are found and immediately presented to the user. This immediate feedback often allows the user to stop short of typing the entire word or phrase they were looking for. The user may also choose a closely related option from the presented list. The method of incremental search is sometimes distinguished from user interfaces that employ a modal window, such as a dialog box, to enter searches. For some applications, a separate user interface mode may be used instead of a dialog box. History The first documented use of incremental search was in EMACS on ITS in the late 1970s. This was one of the many essential Emacs features Richard Stallman included in his reimplementation, GNU Emacs. Other noteworthy programs containing ...
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