Related Research Articles
In a computer language, a reserved word is a word that cannot be used as an identifier, such as the name of a variable, function, or label – it is "reserved from use". This is a syntactic definition, and a reserved word may have no user-define meaning.
In linguistics, a corpus or text corpus is a language resource consisting of a large and structured set of texts. In corpus linguistics, they are used to do statistical analysis and hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory.
A vocabulary is a set of familiar words within a person's language. A vocabulary, usually developed with age, serves as a useful and fundamental tool for communication and acquiring knowledge. Acquiring an extensive vocabulary is one of the largest challenges in learning a second language.
Readability is the ease with which a reader can understand a written text. In natural language, the readability of text depends on its content and its presentation. Researchers have used various factors to measure readability, such as:
Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is concerned with building systems that automatically answer questions posed by humans in a natural language.
Autocomplete, or word completion, is a feature in which an application predicts the rest of a word a user is typing. In Android and iOS smartphones, this is called predictive text. In graphical user interfaces, users can typically press the tab key to accept a suggestion or the down arrow key to accept one of several.
In corpus linguistics, part-of-speech tagging, 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.
Stop words are any word in a stop list which are filtered out before or after processing of natural language data (text). There is no single universal list of stop words used by all natural language processing tools, nor any agreed upon rules for identifying stop words, and indeed not all tools even use such a list. Therefore, any group of words can be chosen as the stop words for a given purpose. The "general trend in [information retrieval] systems over time has been from standard use of quite large stop lists to very small stop lists to no stop list whatsoever"
In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases.
A tag cloud is a novelty visual representation of text data, typically used to depict keyword metadata (tags) on websites, or to visualize free form text. Tags are usually single words, and the importance of each tag is shown with font size or color. This format is useful for quickly perceiving the most prominent terms to determine its relative prominence. Bigger term means greater weight. When used as website navigation aids, the terms are hyperlinked to items associated with the tag.
In corpus linguistics a key word is a word which occurs in a text more often than we would expect to occur by chance alone. Key words are calculated by carrying out a statistical test which compares the word frequencies in a text against their expected frequencies derived in a much larger corpus, which acts as a reference for general language use. Keyness is then the quality a word or phrase has of being "key" in its context.
In computer language design, stropping is a method of explicitly marking letter sequences as having a special property, such as being a keyword, or a certain type of variable or storage location, and thus inhabiting a different namespace from ordinary names ("identifiers"), in order to avoid clashes. Stropping is not used in most modern languages – instead, keywords are reserved words and cannot be used as identifiers. Stropping allows the same letter sequence to be used both as a keyword and as an identifier, and simplifies parsing in that case – for example allowing a variable named if without clashing with the keyword if.
Statistical machine translation (SMT) is a machine translation paradigm where translations are generated on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora. The statistical approach contrasts with the rule-based approaches to machine translation as well as with example-based machine translation.
Studies that estimate and rank the most common words in English examine texts written in English. Perhaps the most comprehensive such analysis is one that was conducted against the Oxford English Corpus (OEC), a very large collection of texts from around the world that are written in the English language. A text corpus is a large collection of written works that are organised in a way that makes such analysis easier.
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.
Search engine indexing is the collecting, parsing, and storing of data to facilitate fast and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics, and computer science. alternate name for the process in the context of search engines designed to find web pages on the Internet is web indexing.
A word list is a list of a language's lexicon within some given text corpus, serving the purpose of vocabulary acquisition. A lexicon sorted by frequency "provides a rational basis for making sure that learners get the best return for their vocabulary learning effort", but is mainly intended for course writers, not directly for learners. Frequency lists are also made for lexicographical purposes, serving as a sort of checklist to ensure that common words are not left out. Some major pitfalls are the corpus content, the corpus register, and the definition of "word". While word counting is a thousand years old, with still gigantic analysis done by hand in the mid-20th century, natural language electronic processing of large corpora such as movie subtitles has accelerated the research field.
The following outline is provided as an overview of and topical guide to natural language processing:
Automatic taxonomy construction (ATC) is the use of software programs to generate taxonomical classifications from a body of texts called a corpus. ATC is a branch of natural language processing, which in turn is a branch of artificial intelligence.
Sketch Engine is a corpus manager and text analysis software developed by Lexical Computing Limited since 2003. Its purpose is to enable people studying language behaviour to search large text collections according to complex and linguistically motivated queries. Sketch Engine gained its name after one of the key features, word sketches: one-page, automatic, corpus-derived summaries of a word's grammatical and collocational behaviour. Currently, it supports and provides corpora in 90+ languages.
References
- ↑ Uberti, H. Z.; Scruggs, T. F.; Mastropieri, M. A. (January 1, 2013). "Keywords Make the Difference!".Cite journal requires
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- Scott, M. & Tribbe, C., 2006, Textual Patterns: keyword and corpus analysis in language education, Amsterdam: Benjamins.
