|
CLAWS (linguistics)
The Constituent Likelihood Automatic Word-tagging System (CLAWS) is a program that performs part-of-speech tagging. It was developed in the 1980s at Lancaster University by the University Centre for Computer Corpus Research on Language. It has an overall accuracy rate of 96-97% with the latest version (CLAWS4) tagging around 100 million words of the British National Corpus. History A Part-Of-Speech Tagger (POS Tagger) is a piece of software that reads text in some language and assigns parts of speech to each word (and other token), such as noun, verb, adjective, etc., although generally computational applications use more fine-grained POS tags like 'noun-plural'. Developed in the early 1980s, CLAWS was built to fill the ever-growing gap created by always-changing POS necessities. Originally created to add part-of-speech tags to the LOB corpus of British English, the CLAWS tagset has since been adapted to other languages as well, including Urdu and Arabic. Since its inception, CLA ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Part-of-speech Tagging
In corpus linguistics, part-of-speech tagging (POS tagging or PoS tagging or POST), also called grammatical tagging is the process of marking up a word in a text (corpus) as corresponding to a particular part of speech, based on both its definition and its context. A simplified form of this is commonly taught to school-age children, in the identification of words as nouns, verbs, adjectives, adverbs, etc. Once performed by hand, POS tagging is now done in the context of computational linguistics, using algorithms which associate discrete terms, as well as hidden parts of speech, by a set of descriptive tags. POS-tagging algorithms fall into two distinctive groups: rule-based and stochastic. E. Brill's tagger, one of the first and most widely used English POS-taggers, employs rule-based algorithms. Principle Part-of-speech tagging is harder than just having a list of words and their parts of speech, because some words can represent more than one part of speech at different times, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lancaster University
Lancaster University (legally The University of Lancaster) is a public university, public research university in Lancaster, Lancashire, Lancaster, Lancashire, England. The university was established in 1964 by royal charter, as one of several plate glass university, new universities created in the 1960s. The university was initially based in St Leonard's Gate in the city centre, before starting a move in 1967 to a purpose-built campus at Bailrigg, to the south. The campus buildings are arranged around a central walkway known as the Spine, which is connected to a central plaza, named Alexandra Square in honour of its first chancellor (education), chancellor, Princess Alexandra, The Honourable Lady Ogilvy, Princess Alexandra. Lancaster is a Colleges within universities in the United Kingdom, residential collegiate university; the colleges are weakly autonomous. The eight undergraduate colleges are named after places in the Historic counties of England, historic county of Lancashi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
British National Corpus
The British National Corpus (BNC) is a 100-million-word text corpus of samples of written and spoken English from a wide range of sources. The corpus covers British English of the late 20th century from a wide variety of genres, with the intention that it be a representative sample of spoken and written British English of that time. It is used in corpus linguistic for analysis of corpora History The project to create the BNC involved the collaboration of three publishers (with the Oxford University Press as the lead collaborator, Longman and W. & R. Chambers), two universities (the University of Oxford and Lancaster University), and the British Library. The creation of the BNC started in 1991 under the management of the BNC consortium, and the project was finished by 1994. There have been no additions of new samples after 1994, but the BNC underwent slight revisions before the release of the second edition BNC World (2001) and the third edition BNC XML Edition (2007). [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lancaster-Oslo-Bergen Corpus
The Lancaster-Oslo/Bergen (LOB) Corpus is a million-word collection of British English texts which was compiled in the 1970s in collaboration between the University of Lancaster, the University of Oslo, and the Norwegian Computing Centre for the Humanities, Bergen, to provide a British counterpart to the Brown Corpus compiled by Henry Kučera and W. Nelson Francis for American English in the 1960s. Its composition was designed to match the original Brown corpus in terms of its size and genres as closely as possible using documents published in the UK by British authors. Both corpora consist of 500 samples each comprising about 2000 words in the following genres: The corpus has been also tagged Tagged may refer to: * Tagged (website), a social discovery website * Tagged (web series), an American teen psychological thriller web series {{disambiguation ..., i.e. part-of-speech categories have been assigned to every word. External links LOB Corpus ManualLOB Corpus from the Oxf ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hidden Markov Model
A hidden Markov model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process — call it X — with unobservable ("''hidden''") states. As part of the definition, HMM requires that there be an observable process Y whose outcomes are "influenced" by the outcomes of X in a known way. Since X cannot be observed directly, the goal is to learn about X by observing Y. HMM has an additional requirement that the outcome of Y at time t=t_0 must be "influenced" exclusively by the outcome of X at t=t_0 and that the outcomes of X and Y at t handwriting recognition, handwriting, gesture recognition, part-of-speech tagging, musical score following, partial discharges and bioinformatics. Definition Let X_n and Y_n be discrete-time stochastic processes and n\geq 1. The pair (X_n,Y_n) is a ''hidden Markov model'' if * X_n is a Markov process whose behavior is not directly observable ("hidden"); * \operatorname\bigl(Y_n \i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bram Stoker
Abraham Stoker (8 November 1847 – 20 April 1912) was an Irish author who is celebrated for his 1897 Gothic horror novel '' Dracula''. During his lifetime, he was better known as the personal assistant of actor Sir Henry Irving and business manager of the Lyceum Theatre, which Irving owned. In his early years, Stoker worked as a theatre critic for an Irish newspaper, and wrote stories as well as commentaries. He also enjoyed travelling, particularly to Cruden Bay where he set two of his novels. During another visit to the English coastal town of Whitby, Stoker drew inspiration for writing ''Dracula''. He died on 20 April 1912 due to locomotor ataxia and was cremated in north London. Since his death, his magnum opus ''Dracula'' has become one of the most well-known works in English literature, and the novel has been adapted for numerous films, short stories, and plays. Early life Stoker was born on 8 November 1847 at 15 Marino Crescent, Clontarf, on the northside of Dubli ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brown Corpus
The Brown University Standard Corpus of Present-Day American English (or just Brown Corpus) is an electronic collection of text samples of American English, the first major structured corpus of varied genres. This corpus first set the bar for the scientific study of the frequency and distribution of word categories in everyday language use. Compiled by Henry Kučera and W. Nelson Francis at Brown University, in Rhode Island, it is a general language corpus containing 500 samples of English, totaling roughly one million words, compiled from works published in the United States in 1961. History In 1967, Kučera and Francis published their classic work ''Computational Analysis of Present-Day American English'', which provided basic statistics on what is known today simply as the ''Brown Corpus''. The Brown Corpus was a carefully compiled selection of current American English, totalling about a million words drawn from a wide variety of sources. Kučera and Francis subjected it to a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bergen Corpus Of London Teenage Language
The Bergen Corpus of London Teenage Language (COLT) is a data set of samples of spoken English that was compiled in 1993 from tape recorded and transcribed conversations by teens between the ages of 13 and 17 in schools throughout London, England. This corpus, which has been tagged for part of speech using the CLAWS 6 tagset, is one of the linguistic research projects housed at the University of Bergen in Norway. Resultant research Linguistic analysis In the study of language, description or descriptive linguistics is the work of objectively analyzing and describing how language is actually used (or how it was used in the past) by a speech community. François & Ponsonnet (2013). All acad ... based on COLT has appeared in the book ''Trends in Teenage Talk'' and subsequent journal articles, including, for example, work tracking ''innit'', ''cos'', degree modifiers, extenders, the use of taboo words,Stenström, Anna-Brita. 2006. Taboo words in teenage talk: London and Madri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brill Tagger
The Brill tagger is an inductive method for part-of-speech tagging. It was described and invented by Eric Brill in his 1993 PhD thesis. It can be summarized as an "error-driven transformation-based tagger". It is: * a form of supervised learning, which aims to minimize error; and, * a transformation-based process, in the sense that a tag is assigned to each word and changed using a set of predefined rules. In the transformation process, if the word is known, it first assigns the most frequent tag, or if the word is unknown, it naively assigns the tag "noun" to it. High accuracy is eventually achieved by applying these rules iteratively and changing the incorrect tags. This approach ensures that valuable information such as the morphosyntactic construction of words is employed in an automatic tagging process. Algorithm The algorithm starts with initialization, which is the assignment of tags based on their probability for each word (for example, "dog" is more often a noun than a v ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Part-of-speech Tagging
In corpus linguistics, part-of-speech tagging (POS tagging or PoS tagging or POST), also called grammatical tagging is the process of marking up a word in a text (corpus) as corresponding to a particular part of speech, based on both its definition and its context. A simplified form of this is commonly taught to school-age children, in the identification of words as nouns, verbs, adjectives, adverbs, etc. Once performed by hand, POS tagging is now done in the context of computational linguistics, using algorithms which associate discrete terms, as well as hidden parts of speech, by a set of descriptive tags. POS-tagging algorithms fall into two distinctive groups: rule-based and stochastic. E. Brill's tagger, one of the first and most widely used English POS-taggers, employs rule-based algorithms. Principle Part-of-speech tagging is harder than just having a list of words and their parts of speech, because some words can represent more than one part of speech at different times, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sliding Window Based Part-of-speech Tagging
Sliding window based part-of-speech tagging is used to part-of-speech tag a text. A high percentage of words in a natural language are 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. Solving this problem is very important in many areas of natural language processing. For example in machine translation changing the part-of-speech of a word can dramatically change its translation. Sliding window based part-of-speech taggers are programs which assign a single part-of-speech to a given lexical form of a word, by looking at a fixed sized "window" of words around the word to be disambiguated. The two main advantages of this approach are: * It is possible to automatically train the tagger, getting rid of the need of manually tagging a corpus. * The tagger can be implemented as a finite state automaton (Mealy machine) Formal definition Let :\Gamma = \ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves. Challenges in natural language processing frequently involve speech recognition, natural-language understanding, and natural-language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
.jpg "Click for more on -> Lancaster University")
_05.jpg "Click for more on -> Brown Corpus")
