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In mathematics and computer science,optimal radix choiceis the problem of choosing the base, orradix, that is best suited for representing numbers. Various proposals have been made to quantify the relative costs of using different radices in representing numbers, especially in computer systems. One formula is the numbe... | https://en.wikipedia.org/wiki/Radix_economy |
Incomputer science,radix sortis a non-comparativesorting algorithm. It avoids comparison by creating anddistributingelements into buckets according to theirradix. For elements with more than onesignificant digit, this bucketing process is repeated for each digit, while preserving the ordering of the prior step, until a... | https://en.wikipedia.org/wiki/Radix_sort |
Non-standard positional numeral systemshere designatesnumeral systemsthat may loosely be described aspositional systems, but that do not entirely comply with the following description of standard positional systems:
This article summarizes facts on some non-standard positional numeral systems. In most cases, the polyn... | https://en.wikipedia.org/wiki/Non-standard_positional_numeral_systems |
There are many differentnumeral systems, that is,writing systemsfor expressingnumbers.
"Abaseis a natural number B whosepowers(B multiplied by itself some number of times) are specially designated within a numerical system."[1]: 38The term is not equivalent toradix, as it applies to all numerical notation systems (not... | https://en.wikipedia.org/wiki/List_of_numeral_systems |
Instatistics, thehypergeometric distributionis the discreteprobability distributiongenerated by picking colored balls at random from anurnwithout replacement.
Various generalizations to this distribution exist for cases where the picking of colored balls isbiasedso that balls of one color are more likely to be picked ... | https://en.wikipedia.org/wiki/Noncentral_hypergeometric_distributions |
N∈{0,1,2,…}{\displaystyle N\in \left\{0,1,2,\dots \right\}}- total number of elementsK∈{0,1,2,…,N}{\displaystyle K\in \left\{0,1,2,\dots ,N\right\}}- total number of 'success' elements
Inprobability theoryandstatistics, thenegative hypergeometric distributiondescribes probabilities for when sampling from a finite popu... | https://en.wikipedia.org/wiki/Negative_hypergeometric_distribution |
Inprobability theory, themultinomial distributionis a generalization of thebinomial distribution. For example, it models the probability of counts for each side of ak-sided die rolledntimes. Fornindependenttrials each of which leads to a success for exactly one ofkcategories, with each category having a given fixed suc... | https://en.wikipedia.org/wiki/Multinomial_distribution |
In thisstatistics,quality assurance, andsurvey methodology,samplingis the selection of a subset or astatistical sample(termedsamplefor short) of individuals from within astatistical populationto estimate characteristics of the whole population. The subset is meant to reflect the whole population, and statisticians atte... | https://en.wikipedia.org/wiki/Sampling_(statistics) |
Inmathematics, ageneralized hypergeometric seriesis apower seriesin which the ratio of successivecoefficientsindexed bynis arational functionofn. The series, if convergent, defines ageneralized hypergeometric function, which may then be defined over a wider domain of the argument byanalytic continuation. The generali... | https://en.wikipedia.org/wiki/Generalized_hypergeometric_function |
Inprobability theory, thecoupon collector's problemrefers to mathematical analysis of "collect allcouponsand win" contests. It asks the following question: if each box of a given product (e.g., breakfast cereals) contains a coupon, and there arendifferent types of coupons, what is the probability that more thantboxes n... | https://en.wikipedia.org/wiki/Coupon_collector%27s_problem |
⌈−1log2(1−p)⌉{\displaystyle \left\lceil {\frac {-1}{\log _{2}(1-p)}}\right\rceil }
⌈−1log2(1−p)⌉−1{\displaystyle \left\lceil {\frac {-1}{\log _{2}(1-p)}}\right\rceil -1}
Inprobability theoryandstatistics, thegeometric distributionis either one of twodiscrete probability distributions:
These two different geometric... | https://en.wikipedia.org/wiki/Geometric_distribution |
Keno/kiːnoʊ/is alottery-like gambling game often played at moderncasinos, and also offered as a game in some lotteries.
Players wager by choosing numbers ranging from 1 through (usually) 80. After all players make their wagers, 20 numbers (some variants draw fewer numbers) are drawn at random, either with a ball machi... | https://en.wikipedia.org/wiki/Keno |
In thedesign of experimentsinstatistics, thelady tasting teais arandomized experimentdevised byRonald Fisherand reported in his bookThe Design of Experiments(1935).[1]The experiment is the original exposition of Fisher's notion of anull hypothesis, which is "never proved or established, but is possibly disproved, in th... | https://en.wikipedia.org/wiki/Lady_tasting_tea |
Incomputer science, aparsing expression grammar(PEG) is a type ofanalyticformal grammar, i.e. it describes aformal languagein terms of a set of rules for recognizingstringsin the language. The formalism was introduced by Bryan Ford in 2004[1]and is closely related to the family oftop-down parsing languagesintroduced in... | https://en.wikipedia.org/wiki/Parsing_expression_grammar |
Intheoretical linguisticsandcomputational linguistics,probabilistic context free grammars(PCFGs) extendcontext-free grammars, similar to howhidden Markov modelsextendregular grammars. Eachproductionis assigned a probability. The probability of a derivation (parse) is the product of the probabilities of the productions ... | https://en.wikipedia.org/wiki/Stochastic_context-free_grammar |
Astraight-line grammar(sometimes abbreviated as SLG) is aformal grammarthat generates exactly one string.[1]Consequently, it does not branch (every non-terminal has only one associated production rule) nor loop (if non-terminalAappears in a derivation ofB, thenBdoes not appear in a derivation ofA).[1]
Straight-line gr... | https://en.wikipedia.org/wiki/Context-free_grammar_generation_algorithms |
Incomputer science, in particular informal language theory, thepumping lemmafor context-free languages, also known as theBar-Hillellemma,[1]is alemmathat gives a property shared by allcontext-free languagesand generalizes thepumping lemma for regular languages.
The pumping lemma can be used to construct arefutation by... | https://en.wikipedia.org/wiki/Pumping_lemma_for_context-free_languages |
Incomputer science,Backus–Naur form(BNF, pronounced/ˌbækəsˈnaʊər/), also known asBackus normal form, is a notation system for defining thesyntaxofprogramming languagesand otherformal languages, developed byJohn BackusandPeter Naur. It is ametasyntaxforcontext-free grammars, providing a precise way to outline the rules ... | https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_form |
Incomputer science, theCocke–Younger–Kasami algorithm(alternatively calledCYK, orCKY) is aparsingalgorithmforcontext-free grammarspublished by Itiroo Sakai in 1961.[1][2]The algorithm is named after some of its rediscoverers:John Cocke, Daniel Younger,Tadao Kasami, andJacob T. Schwartz. It employsbottom-up parsinganddy... | https://en.wikipedia.org/wiki/CYK_algorithm |
Informal languagetheory, acontext-free grammaris inGreibach normal form(GNF) if the right-hand sides of allproductionrules start with aterminal symbol, optionally followed by some non-terminals. A non-strict form allows one exception to this format restriction for allowing theempty word(epsilon, ε) to be a member of th... | https://en.wikipedia.org/wiki/Greibach_normal_form |
Informal language theory, anoncontracting grammaris inKuroda normal formif all production rules are of the form:[1]
where A, B, C and D arenonterminalsymbols andais aterminal symbol.[1]Some sources omit theA→Bpattern.[2]
It is named afterSige-Yuki Kuroda, who originally called it alinear bounded grammar, a terminolog... | https://en.wikipedia.org/wiki/Kuroda_normal_form |
Combinatorics on wordsis a fairly new field ofmathematics, branching fromcombinatorics, which focuses on the study ofwordsandformal languages. The subject looks at letters orsymbols, and thesequencesthey form.Combinatorics on wordsaffects various areas of mathematical study, includingalgebraandcomputer science. There... | https://en.wikipedia.org/wiki/Combinatorics_on_words |
Incomputer science,formal methodsaremathematicallyrigorous techniques for thespecification, development,analysis, andverificationofsoftwareandhardwaresystems.[1]The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate ma... | https://en.wikipedia.org/wiki/Formal_method |
Inabstract algebra, thefree monoidon asetis themonoidwhose elements are all thefinite sequences(or strings) of zero or more elements from that set, withstring concatenationas the monoid operation and with the unique sequence of zero elements, often called theempty stringand denoted by ε or λ, as theidentity element. Th... | https://en.wikipedia.org/wiki/Free_monoid |
Inlinguistics,grammaris the set of rules for how anatural languageis structured, as demonstrated by its speakers orwriters. Grammar rules may concern the use ofclauses,phrases, andwords. The term may also refer to the study of such rules, a subject that includesphonology,morphology, andsyntax, together withphonetics,se... | https://en.wikipedia.org/wiki/Grammar_framework |
Mathematical notationconsists of usingsymbolsfor representingoperations, unspecifiednumbers,relations, and any othermathematical objectsand assembling them intoexpressionsandformulas. Mathematical notation is widely used inmathematics,science, andengineeringfor representing complexconceptsandpropertiesin a concise, una... | https://en.wikipedia.org/wiki/Mathematical_notation |
Incomputer programming, astringis traditionally asequenceofcharacters, either as aliteral constantor as some kind ofvariable. The latter may allow its elements to bemutatedand the length changed, or it may be fixed (after creation). A string is often implemented as anarray data structureofbytes(orwords) that stores a s... | https://en.wikipedia.org/wiki/String_(computer_science) |
Language acquisitionis the process by which humans acquire the capacity to perceive and comprehendlanguage. In other words, it is how human beings gain the ability to be aware of language, to understand it, and to produce and usewordsandsentencesto communicate.
Language acquisition involves structures, rules, and repr... | https://en.wikipedia.org/wiki/Language_acquisition |
Theorigin of language, its relationship withhuman evolution, and its consequences have been subjects of study for centuries. Scholars wishing to study the origins of language draw inferences from evidence such as thefossil record,archaeological evidence, and contemporary language diversity. They may also studylanguage ... | https://en.wikipedia.org/wiki/Origin_of_language |
Formal semanticsis the study ofgrammaticalmeaning innatural languagesusingformalconcepts fromlogic,mathematicsandtheoretical computer science. It is an interdisciplinary field, sometimes regarded as a subfield of bothlinguisticsandphilosophy of language. It provides accounts of what linguistic expressions mean and how ... | https://en.wikipedia.org/wiki/Formal_semantics_(natural_language) |
Whistled languagesare linguistic systems that usewhistlingas a form of speech and facilitate communication between individuals. More than 80 languages have been found to practice various degrees of whistling, most of them in rugged topography or dense forests, where whistling expands the area of communication while mov... | https://en.wikipedia.org/wiki/Whistled_language |
Andrey Andreyevich Markov[a](14 June 1856 – 20 July 1922) was a Russian mathematician best known for his work onstochastic processes. A primary subject of his research later became known as theMarkov chain. He was also a strong, close to master-level, chess player.
Markov and his younger brotherVladimir Andreyevich Ma... | https://en.wikipedia.org/wiki/Andrey_Markov |
Bayesian inference(/ˈbeɪziən/BAY-zee-ənor/ˈbeɪʒən/BAY-zhən)[1]is a method ofstatistical inferencein whichBayes' theoremis used to calculate a probability of a hypothesis, given priorevidence, and update it as moreinformationbecomes available. Fundamentally, Bayesian inference uses aprior distributionto estimateposterio... | https://en.wikipedia.org/wiki/Bayesian_inference |
Richard J. Boys(6 April 1960 – 5 March 2019) was a statistician best known for his contributions to theBayesian inference,hidden Markov modelsand stochastic systems.[1]
Richard attended Newcastle University where he obtained a BSc in mathematics in 1981. He went on to do a Master's and a doctorate at theUniversity of ... | https://en.wikipedia.org/wiki/Richard_James_Boys |
Conditional random fields(CRFs) are a class ofstatistical modeling methodsoften applied inpattern recognitionandmachine learningand used forstructured prediction. Whereas aclassifierpredicts a label for a single sample without considering "neighbouring" samples, a CRF can take context into account. To do so, the predic... | https://en.wikipedia.org/wiki/Conditional_random_field |
Estimation theoryis a branch ofstatisticsthat deals with estimating the values ofparametersbased on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects the distribution of the measured data. Anestimatorattempts to approximat... | https://en.wikipedia.org/wiki/Estimation_theory |
TheHH-suiteis anopen-source softwarepackage for sensitiveproteinsequence searching. It contains programs that can search for similar protein sequences in protein sequence databases. Sequence searches are a standard tool in modern biology with which the function of unknown proteins can be inferred from the functions of ... | https://en.wikipedia.org/wiki/HH-suite |
HMMERis afreeand commonly used software package for sequence analysis written bySean Eddy.[2]Its general usage is to identifyhomologousproteinornucleotidesequences, and to perform sequence alignments. It detects homology by comparing aprofile-HMM(aHidden Markov modelconstructed explicitly for a particular search) to e... | https://en.wikipedia.org/wiki/HMMER |
Time-inhomogeneous hiddenBernoullimodel (TI-HBM)is an alternative tohidden Markov model(HMM) forautomatic speech recognition. Contrary to HMM, the state transition process in TI-HBM is not aMarkov-dependent process, rather it is ageneralized Bernoulli(an independent) process. This difference leads to elimination ofdyna... | https://en.wikipedia.org/wiki/Hidden_Bernoulli_model |
Ahidden semi-Markov model(HSMM) is a statistical model with the same structure as ahidden Markov modelexcept that the unobservable process issemi-Markovrather thanMarkov. This means that the probability of there being a change in the hidden state depends on the amount of time that has elapsed since entry into the curre... | https://en.wikipedia.org/wiki/Hidden_semi-Markov_model |
Thehierarchical hidden Markov model (HHMM)is astatistical modelderived from thehidden Markov model(HMM). In an HHMM, each state is considered to be a self-containedprobabilistic model. More precisely, each state of the HHMM is itself an HHMM.
HHMMs and HMMs are useful in many fields, includingpattern recognition.[1][2... | https://en.wikipedia.org/wiki/Hierarchical_hidden_Markov_model |
Thelayeredhidden Markov model(LHMM)is astatistical modelderived from the hidden Markov model (HMM).
A layered hidden Markov model (LHMM) consists ofNlevels of HMMs, where the HMMs on leveli+ 1 correspond to observation symbols or probability generators at leveli.
Every leveliof the LHMM consists ofKiHMMs running in pa... | https://en.wikipedia.org/wiki/Layered_hidden_Markov_model |
Sequential dynamical systems(SDSs) are a class ofgraph dynamical systems. They are discretedynamical systemswhich generalize many aspects of for example classicalcellular automata, and they provide a framework for studying asynchronous processes overgraphs. The analysis of SDSs uses techniques fromcombinatorics,abstrac... | https://en.wikipedia.org/wiki/Sequential_dynamical_system |
Inmathematics, atime seriesis a series ofdata pointsindexed (or listed or graphed) in time order. Most commonly, a time series is asequencetaken at successive equally spaced points in time. Thus it is a sequence ofdiscrete-timedata. Examples of time series are heights of oceantides, counts ofsunspots, and the daily cl... | https://en.wikipedia.org/wiki/Time_series |
In the mathematical theory ofstochastic processes,variable-order Markov (VOM) modelsare an important class of models that extend the well knownMarkov chainmodels. In contrast to the Markov chain models, where eachrandom variablein a sequence with aMarkov propertydepends on a fixed number of random variables, in VOM mod... | https://en.wikipedia.org/wiki/Variable-order_Markov_model |
Sliding window based part-of-speech taggingis used topart-of-speech taga text.
A high percentage of words in anatural languageare words which out of context can be assigned more than one part of speech. The percentage of these ambiguous words is typically around 30%, although it depends greatly on the language. Solvin... | https://en.wikipedia.org/wiki/Sliding_window_based_part-of-speech_tagging |
Traditional grammar(also known asclassical grammar) is a framework for the description of the structure of alanguageor group of languages.[1]The roots of traditional grammar are in the work of classicalGreekandLatinphilologists.[2]The formal study ofgrammarbased on these models became popular during the Renaissance.[3]... | https://en.wikipedia.org/wiki/Traditional_grammar |
Aclassifier(abbreviatedclf[1]orcl) is awordoraffixthat accompaniesnounsand can be considered to "classify" a noun depending on some characteristics (e.g. humanness, animacy, sex, shape, social status) of itsreferent.[2][3]Classifiers in this sense are specifically callednoun classifiersbecause some languages inPapuaas ... | https://en.wikipedia.org/wiki/Classifier_(linguistics) |
Informal semanticsconservativityis a proposedlinguistic universalwhich states that anydeterminerD{\displaystyle D}must obey the equivalenceD(A,B)↔D(A,A∩B){\displaystyle D(A,B)\leftrightarrow D(A,A\cap B)}. For instance, theEnglishdeterminer "every" can be seen to be conservative by theequivalenceof the following two se... | https://en.wikipedia.org/wiki/Conservativity |
Inlinguistics,determiner spreading(DS), also known as Multiple or Double Determiners[1]is the appearance of more than onedeterminerassociated with anoun phrase, usually marking anadjectiveas well as thenounitself.[2]The extra determiner has been called an adjectival determiner[3]because determiner spreading is most com... | https://en.wikipedia.org/wiki/Determiner_spreading |
English determiners(also known asdeterminatives)[1]: 354arewords– such asthe,a,each,some,which,this, and numerals such assix– that are most commonly used withnounsto specify theirreferents. Thedeterminersform a closedlexical categoryinEnglish.[2]
The syntactic role characteristically performed by determiners is known ... | https://en.wikipedia.org/wiki/English_determiners |
Asemantic network, orframe networkis aknowledge basethat representssemanticrelations betweenconceptsin a network. This is often used as a form ofknowledge representation. It is adirectedorundirected graphconsisting ofvertices, which representconcepts, andedges, which representsemantic relationsbetweenconcepts,[1]mappin... | https://en.wikipedia.org/wiki/Semantic_net |
Incomputational linguistics, atrigram taggeris a statistical method forautomatically identifying words as being nouns, verbs, adjectives, adverbs, etc.based on second orderMarkov modelsthat consider triples of consecutive words. It is trained on atext corpusas a method to predict the next word, taking the product of t... | https://en.wikipedia.org/wiki/Trigram_tagger |
Word-sense disambiguationis the process of identifying whichsenseof awordis meant in asentenceor other segment ofcontext. In humanlanguage processingandcognition, it is usually subconscious.
Given that natural language requires reflection of neurological reality, as shaped by the abilities provided by the brain'sneura... | https://en.wikipedia.org/wiki/Word_sense_disambiguation |
Adversarial information retrieval(adversarial IR) is a topic ininformation retrievalrelated to strategies for working with a data source where some portion of it has been manipulated maliciously. Tasks can include gathering, indexing, filtering, retrieving and ranking information from such a data source. Adversarial I... | https://en.wikipedia.org/wiki/Adversarial_information_retrieval |
Computer memorystores information, such as data and programs, for immediate use in thecomputer.[2]The termmemoryis often synonymous with the termsRAM,main memory,orprimary storage.Archaic synonyms for main memory includecore(for magnetic core memory) andstore.[3]
Main memory operates at a high speed compared tomass st... | https://en.wikipedia.org/wiki/Computer_memory |
Controlled vocabulariesprovide a way to organize knowledge for subsequent retrieval. They are used insubject indexingschemes,subject headings,thesauri,[1][2]taxonomiesand otherknowledge organization systems. Controlled vocabulary schemes mandate the use of predefined, preferred terms that have been preselected by the ... | https://en.wikipedia.org/wiki/Controlled_vocabulary |
Cross-language information retrieval(CLIR) is a subfield ofinformation retrievaldealing with retrieving information written in a language different from the language of the user's query.[1]The term "cross-language information retrieval" has many synonyms, of which the following are perhaps the most frequent: cross-ling... | https://en.wikipedia.org/wiki/Cross-language_information_retrieval |
Data miningis the process of extracting and finding patterns in massivedata setsinvolving methods at the intersection ofmachine learning,statistics, anddatabase systems.[1]Data mining is aninterdisciplinarysubfield ofcomputer scienceandstatisticswith an overall goal of extracting information (with intelligent methods) ... | https://en.wikipedia.org/wiki/Data_mining |
Data retrievalmeans obtaining data from adatabase management system(DBMS), like for example anobject-oriented database(ODBMS). In this case, it is considered that data is represented in astructuredway, and there is noambiguityin data.
In order to retrieve the desired data the user presents a set of criteria by aquery.... | https://en.wikipedia.org/wiki/Data_retrieval |
TheEuropean Summer School in Information Retrieval(ESSIR) is a scientific event founded in 1990, which starts off a series ofsummer schoolsto teach aboutinformation retrieval. ESSIR is typically a week-long event consisting of guest lectures and seminars from invited lecturers.Maristella Agostiin 2008 stated that: "The... | https://en.wikipedia.org/wiki/European_Summer_School_in_Information_Retrieval |
Human–computer information retrieval(HCIR) is the study and engineering ofinformation retrievaltechniques that bring human intelligence into thesearchprocess. It combines the fields ofhuman-computer interaction(HCI) and information retrieval (IR) and creates systems that improve search by taking into account the human ... | https://en.wikipedia.org/wiki/Human%E2%80%93computer_information_retrieval |
Information seekingis the process or activity of attempting to obtain information in both human and technological contexts. Information seeking is related to, but different from,information retrieval(IR).
Traditionally, IR tools have been designed for IR professionals to enable them to effectively and efficiently retr... | https://en.wikipedia.org/wiki/Information_seeking |
Information seekingis the process or activity of attempting to obtain information in both human and technological contexts. Information seeking is related to, but different from,information retrieval(IR).
Traditionally, IR tools have been designed for IR professionals to enable them to effectively and efficiently retr... | https://en.wikipedia.org/wiki/Information_seeking#Compared_to_information_retrieval |
Collaborative information seeking(CIS) is a field of research that involves studying situations, motivations, and methods for people working in collaborative groups for information seeking projects, as well as building systems for supporting such activities. Such projects often involve information searching orinformati... | https://en.wikipedia.org/wiki/Collaborative_information_seeking |
Social information seekingis a field of research that involves studying situations, motivations, and methods for people seeking and sharing information in participatory online social sites, such asYahoo! Answers, Answerbag,WikiAnswersandTwitteras well as building systems for supporting such activities. Highly related t... | https://en.wikipedia.org/wiki/Social_information_seeking |
TheInformation Retrieval Facility(IRF), founded 2006 and located inVienna,Austria, was a research platform for networking and collaboration for professionals in the field ofinformation retrieval. It ceased operations in 2012. | https://en.wikipedia.org/wiki/Information_Retrieval_Facility |
Visualization(orvisualisation), also known asgraphics visualization, is any technique for creatingimages,diagrams, oranimationsto communicate a message. Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of humanity. from history includecave pai... | https://en.wikipedia.org/wiki/Knowledge_visualization |
Multimedia information retrieval(MMIRorMIR) is a research discipline ofcomputer sciencethat aims at extracting semantic information frommultimediadata sources.[1][failed verification]Data sources include directly perceivable media such asaudio,imageandvideo, indirectly perceivable sources such astext, semantic descript... | https://en.wikipedia.org/wiki/Multimedia_information_retrieval |
Personal information management(PIM) is the study and implementation of the activities that people perform in order to acquire or create, store, organize, maintain, retrieve, and useinformationalitems such asdocuments(paper-based and digital),web pages, andemailmessages for everyday use to complete tasks (work-related ... | https://en.wikipedia.org/wiki/Personal_information_management |
Pearl growingis ametaphortaken from the process of small bits of sand growing to make a beautiful pearl, which is used ininformation literacy. This is also called "snowballing",[1]alluding to the process of how a snowball can grow into a big snow-man by accumulating snow. In this context this refers to the process of u... | https://en.wikipedia.org/wiki/Pearl_growing |
Query understandingis the process of inferring theintentof asearch engineuser by extracting semantic meaning from the searcher’s keywords.[1]Query understanding methods generally take place before the search engineretrievesandranksresults. It is related tonatural language processingbut specifically focused on the under... | https://en.wikipedia.org/wiki/Query_understanding |
Ininformation scienceandinformation retrieval,relevancedenotes how well a retrieved document or set of documents meets theinformation needof the user. Relevance may include concerns such as timeliness, authority or novelty of the result.
The concern with the problem of finding relevant information dates back at least ... | https://en.wikipedia.org/wiki/Relevance_(information_retrieval) |
Relevance feedbackis a feature of someinformation retrievalsystems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather userfeedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distingui... | https://en.wikipedia.org/wiki/Relevance_feedback |
Inmachine learning, anearest centroid classifierornearest prototype classifieris aclassification modelthat assigns to observations the label of the class of training samples whosemean(centroid) is closest to the observation. When applied totext classificationusingword vectorscontainingtf*idfweights to represent documen... | https://en.wikipedia.org/wiki/Nearest_centroid_classifier |
Search engine indexingis the collecting,parsing, and storing of data to facilitate fast and accurateinformation retrieval. Index design incorporates interdisciplinary concepts fromlinguistics,cognitive psychology, mathematics,informatics, andcomputer science. An alternate name for the process, in the context ofsearch e... | https://en.wikipedia.org/wiki/Search_engine_indexing |
SIGIRis theAssociation for Computing Machinery'sSpecial Interest Group on Information Retrieval. The scope of the group's specialty is the theory and application of computers to the acquisition, organization, storage,retrievaland distribution of information; emphasis is placed on working with non-numeric information, r... | https://en.wikipedia.org/wiki/Special_Interest_Group_on_Information_Retrieval |
Subject indexingis the act of describing orclassifyingadocumentbyindex terms, keywords, or other symbols in order to indicate what different documents areabout, to summarize theircontentsor to increasefindability. In other words, it is about identifying and describing thesubjectof documents. Indexes are constructed, se... | https://en.wikipedia.org/wiki/Subject_indexing |
Temporal information retrieval(T-IR) is an emerging area of research related to the field ofinformation retrieval(IR) and a considerable number of sub-areas, positioning itself, as an important dimension in the context of the user information needs.
According toinformation theoryscience (Metzger, 2007),[1]timeliness o... | https://en.wikipedia.org/wiki/Temporal_information_retrieval |
Ininformation retrieval,tf–idf(alsoTF*IDF,TFIDF,TF–IDF, orTf–idf), short forterm frequency–inverse document frequency, is a measure of importance of a word to adocumentin a collection orcorpus, adjusted for the fact that some words appear more frequently in general.[1]Like the bag-of-words model, it models a document ... | https://en.wikipedia.org/wiki/Tf%E2%80%93idf |
XML retrieval, orXML information retrieval, is the content-based retrieval of documents structured withXML(eXtensible Markup Language). As such it is used for computingrelevanceof XML documents.[1]
Most XML retrieval approaches do so based on techniques from theinformation retrieval(IR) area, e.g. by computing the sim... | https://en.wikipedia.org/wiki/XML_retrieval |
Data miningis the process of extracting and finding patterns in massivedata setsinvolving methods at the intersection ofmachine learning,statistics, anddatabase systems.[1]Data mining is aninterdisciplinarysubfield ofcomputer scienceandstatisticswith an overall goal of extracting information (with intelligent methods) ... | https://en.wikipedia.org/wiki/Web_mining |
Achampion list, also calledtop docorfancy listis a precomputed list sometimes used with thevector space modelto avoid computing relevancy rankings for all documents each time a document collection is queried. The champion list contains a set of n documents with the highest weights for the given term. The number n can b... | https://en.wikipedia.org/wiki/Champion_list |
Compound-term processing,ininformation-retrieval, is search result matching on the basis ofcompound terms. Compound terms are built by combining two or more simple terms; for example, "triple" is a single word term, but "triple heart bypass" is a compound term.
Compound-term processing is a new approach to an old prob... | https://en.wikipedia.org/wiki/Compound_term_processing |
Aconceptual spaceis a geometric structure that represents a number ofqualitydimensions, which denote basic features by which concepts and objects can be compared, such asweight,color,taste,temperature,pitch, and thethree ordinary spatial dimensions.[1][2]: 4In a conceptual space,pointsdenote objects, andregionsdenote c... | https://en.wikipedia.org/wiki/Conceptual_space |
Sparse distributed memory(SDM) is a mathematical model of humanlong-term memoryintroduced byPentti Kanervain 1988 while he was atNASA Ames Research Center.[1]
This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines – e.g., rapid recognition of faces or ... | https://en.wikipedia.org/wiki/Sparse_distributed_memory |
Innatural language processingaw-shinglingis a set ofuniqueshingles(thereforen-grams) each of which is composed of contiguoussubsequencesoftokenswithin adocument, which can then be used to ascertain thesimilarity between documents. The symbolwdenotes the quantity of tokens in each shingle selected, or solved for.
The ... | https://en.wikipedia.org/wiki/W-shingling |
Instatistics, theuncertainty coefficient, also calledproficiency,entropy coefficientorTheil's U, is a measure of nominalassociation. It was first introduced byHenri Theil[citation needed]and is based on the concept ofinformation entropy.
Suppose we have samples of two discrete random variables,XandY. By constructing... | https://en.wikipedia.org/wiki/Uncertainty_coefficient |
Inmedicineandstatistics,sensitivity and specificitymathematically describe the accuracy of a test that reports the presence or absence of a medical condition. If individuals who have the condition are considered "positive" and those who do not are considered "negative", then sensitivity is a measure of how well a test ... | https://en.wikipedia.org/wiki/Sensitivity_and_specificity |
In the field ofmachine learningand specifically the problem ofstatistical classification, aconfusion matrix, also known aserror matrix,[1]is a specifictablelayout that allows visualization of the performance of an algorithm, typically asupervised learningone; inunsupervised learningit is usually called amatching matrix... | https://en.wikipedia.org/wiki/Confusion_matrix |
Indecision theory, ascoring rule[1]provides evaluation metrics forprobabilistic predictions or forecasts. While "regular" loss functions (such asmean squared error) assign a goodness-of-fit score to a predicted value and an observed value, scoring rules assign such a score to a predicted probability distribution and an... | https://en.wikipedia.org/wiki/Scoring_rule |
Thebase rate fallacy, also calledbase rate neglect[2]orbase rate bias, is a type offallacyin which people tend to ignore thebase rate(e.g., generalprevalence) in favor of the individuating information (i.e., information pertaining only to a specific case).[3]For example, if someone hears that a friend is very shy and q... | https://en.wikipedia.org/wiki/Base_rate_fallacy |
BLEU(bilingual evaluation understudy) is an algorithm forevaluatingthe quality of text which has beenmachine-translatedfrom onenatural languageto another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translati... | https://en.wikipedia.org/wiki/BLEU |
Evaluation of abinary classifiertypically assigns a numerical value, or values, to a classifier that represent its accuracy. An example is error rate, which measures how frequently the classifier makes a mistake.
There are many metrics that can be used; different fields have different preferences. For example, in medi... | https://en.wikipedia.org/wiki/Evaluation_of_binary_classifiers#Single_metrics |
METEOR(Metric for Evaluation of Translation with Explicit ORdering) is ametricfor theevaluation of machine translation output. The metric is based on theharmonic meanof unigramprecision and recall, with recall weighted higher than precision. It also has several features that are not found in other metrics, such asstemm... | https://en.wikipedia.org/wiki/METEOR |
NISTis a method forevaluating the qualityof text which has been translated usingmachine translation. Its name comes from the USNational Institute of Standards and Technology.
It is based on theBLEUmetric, but with some alterations. WhereBLEUsimply calculatesn-gramprecision adding equal weight to each one, NIST also ca... | https://en.wikipedia.org/wiki/NIST_(metric) |
Areceiver operating characteristic curve, orROC curve, is agraphical plotthat illustrates the performance of abinary classifiermodel (can be used for multi class classification as well) at varying threshold values. ROC analysis is commonly applied in the assessment of diagnostic test performance in clinical epidemiolog... | https://en.wikipedia.org/wiki/Receiver_operating_characteristic |
ROUGE, orRecall-Oriented Understudy for Gisting Evaluation,[1]is a set of metrics and a software package used for evaluatingautomatic summarizationandmachine translationsoftware innatural language processing. The metrics compare an automatically produced summary or translation against a reference or a set of references... | https://en.wikipedia.org/wiki/ROUGE_(metric) |
Word error rate(WER) is a common metric of the performance of aspeech recognitionormachine translationsystem. The WER metric typically ranges from 0 to 1, where 0 indicates that the compared pieces of text are exactly identical, and 1 (or larger) indicates that they are completely different with no similarity. This way... | https://en.wikipedia.org/wiki/Word_error_rate |
LEPOR(Length Penalty,Precision, n-gramPosition difference Penalty andRecall) is an automatic language independentmachine translation evaluationmetric with tunable parameters and reinforced factors.
SinceIBMproposed and realized the system ofBLEU[1]as the automatic metric forMachine Translation(MT) evaluation,[2]many o... | https://en.wikipedia.org/wiki/LEPOR |
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