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Automatic Taxonomy Construction
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. A taxonomy (or taxonomical classification) is a scheme of classification, especially, a hierarchical classification, in which things are organized into groups or types. Among other things, a taxonomy can be used to organize and index knowledge (stored as documents, articles, videos, etc.), such as in the form of a library classification system, or a search engine taxonomy, so that users can more easily find the information they are searching for. Many taxonomies are hierarchies (and thus, have an intrinsic tree structure), but not all are. Manually developing and maintaining a taxonomy is a labor-intensive task requiring significant time and resources, including familiarity of or expertise in the taxonomy's domain (scope, subject, or ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Corpus
In linguistics, a corpus (plural ''corpora'') or text corpus is a language resource consisting of a large and structured set of texts (nowadays usually electronically stored and processed). In corpus linguistics, they are used to do statistical analysis and statistical hypothesis testing, hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory. In Search engine (computing), search technology, a corpus is the collection of documents which is being searched. Overview A corpus may contain texts in a single language (''monolingual corpus'') or text data in multiple languages (''multilingual corpus''). In order to make the corpora more useful for doing linguistic research, they are often subjected to a process known as annotation. An example of annotating a corpus is part-of-speech tagging, or ''POS-tagging'', in which information about each word's part of speech (verb, noun, adjective, etc.) is added to the corpus in the form o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Neural Networks
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. Typically, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Information Extraction
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP). Recent activities in multimedia document processing like automatic annotation and content extraction out of images/audio/video/documents could be seen as information extraction Due to the difficulty of the problem, current approaches to IE (as of 2010) focus on narrowly restricted domains. An example is the extraction from newswire reports of corporate mergers, such as denoted by the formal relation: :\mathrm(company_1, company_2, date), from an online news sentence such as: :''"Yesterday, New York based Foo Inc. announced their acquisition of Bar Corp."'' A broad goal of IE is to allow computation to be done on the previously unstructured data. A more sp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Document Classification
Document classification or document categorization is a problem in library science, information science and computer science. The task is to assign a document to one or more classes or categories. This may be done "manually" (or "intellectually") or algorithmically. The intellectual classification of documents has mostly been the province of library science, while the algorithmic classification of documents is mainly in information science and computer science. The problems are overlapping, however, and there is therefore interdisciplinary research on document classification. The documents to be classified may be texts, images, music, etc. Each kind of document possesses its special classification problems. When not otherwise specified, text classification is implied. Documents may be classified according to their subjects or according to other attributes (such as document type, author, printing year etc.). In the rest of this article only subject classification is considered. T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wordnet
WordNet is a lexical database of semantic relations between words in more than 200 languages. WordNet links words into semantic relations including synonyms, hyponyms, and meronyms. The synonyms are grouped into '' synsets'' with short definitions and usage examples. WordNet can thus be seen as a combination and extension of a dictionary and thesaurus. While it is accessible to human users via a web browser, its primary use is in automatic text analysis and artificial intelligence applications. WordNet was first created in the English language and the English WordNet database and software tools have been released under a BSD style license and are freely available for download from that WordNet website. History and team members WordNet was first created in English only in the Cognitive Science Laboratory of Princeton University under the direction of psychology professor George Armitage Miller starting in 1985 and was later directed by Christiane Fellbaum. The project was ini ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ontology (information Science)
In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject. Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. Each uses ontological assumptions to frame explicit theories, research and applications. New ontologies may improve problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. For instance, the definition and ontology of economics is a primary concern in Marxist econo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ontology Learning
Ontology learning (ontology extraction, ontology generation, or ontology acquisition) is the automatic or semi-automatic creation of ontology (information science), ontologies, including extracting the corresponding Domain of discourse, domain's terms and the relationships between the Conceptualization (information science), concepts that these terms represent from a Text corpus, corpus of natural language text, and encoding them with an ontology language for easy retrieval. As ontology engineering, building ontologies manually is extremely labor-intensive and time-consuming, there is great motivation to automate the process. Typically, the process starts by terminology extraction, extracting terms and concepts or noun phrases from plain text using linguistic processors such as part-of-speech tagging and phrase chunking. Then statistical or symbolic techniques are used to extract relation signatures, often based on pattern-based or definition-based hypernym extraction techniques. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Is-a
In knowledge representation, object-oriented programming and design (see object-oriented program architecture), is-a (is_a or is a) is a subsumption relationship between abstractions (e.g. types, classes), wherein one class ''A'' is a subclass of another class ''B'' (and so ''B'' is a superclass of ''A''). In other words, type A is a subtype of type B when A's specification implies B's specification. That is, any object (or class) that satisfies A's specification also satisfies B's specification, because B's specification is weaker. The ''is-a'' relationship is to be contrasted with the ''has-a'' (''has_a'' or ''has a'') relationship between types (classes); confusing the relations ''has-a'' and ''is-a'' is a common error when designing a model (e.g., a computer program) of the real-world relationship between an object and its subordinate. The ''is-a'' relationship may also be contrasted with the '' instance-of'' relationship between objects (instances) and types (classes): se ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linguistics
Linguistics is the scientific study of human language. It is called a scientific study because it entails a comprehensive, systematic, objective, and precise analysis of all aspects of language, particularly its nature and structure. Linguistics is concerned with both the cognitive and social aspects of language. It is considered a scientific field as well as an academic discipline; it has been classified as a social science, natural science, cognitive science,Thagard, PaulCognitive Science, The Stanford Encyclopedia of Philosophy (Fall 2008 Edition), Edward N. Zalta (ed.). or part of the humanities. Traditional areas of linguistic analysis correspond to phenomena found in human linguistic systems, such as syntax (rules governing the structure of sentences); semantics (meaning); morphology (structure of words); phonetics (speech sounds and equivalent gestures in sign languages); phonology (the abstract sound system of a particular language); and pragmatics (how social con ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hypernym And Hyponym
Hypernymy and hyponymy are the semantic relations between a generic term (hypernym) and a specific instance of it (hyponym). The hypernym is also called a supertype, umbrella term, or blanket term. The hyponym is a subtype of the hypernym. The semantic field of the hyponym is included within that of the hypernym. For example, ''pigeon'', ''crow'', and ''hen'' are all hyponyms of ''bird'' and ''animal''; ''bird'' and ''animal'' are both hypernyms of ''pigeon, crow,'' and ''hen''. Hypernyms and Hyponyms In linguistics, semantics, general semantics, and ontologies, hyponymy () shows the relationship between a generic term (hypernym) and a specific instance of it (hyponym). A hyponym is a word or phrase whose semantic field is more specific than its hypernym. The semantic field of a hypernym, also known as a superordinate, is broader than that of a hyponym. An approach to the relationship between hyponyms and hypernyms is to view a hypernym as consisting of hyponyms. This, however ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hyponymy
In linguistics, semantics, general semantics, and ontologies, hyponymy () is a semantic relation between a hyponym denoting a subtype and a hypernym or hyperonym (sometimes called umbrella term or blanket term) denoting a supertype. In other words, the semantic field of the hyponym is included within that of the hypernym. In simpler terms, a hyponym is in a ''type-of'' relationship with its hypernym. For example, ''pigeon'', ''crow'', ''eagle'', and ''seagull'' are all hyponyms of ''bird'', their hypernym, which itself is a hyponym of ''animal'', its hypernym. Hyponyms and hypernyms Hyponymy shows the relationship between a generic term (hypernym) and a specific instance of it (hyponym). A hyponym is a word or phrase whose semantic field is more specific than its hypernym. The semantic field of a hypernym, also known as a superordinate, is broader than that of a hyponym. An approach to the relationship between hyponyms and hypernyms is to view a hypernym as consisting of hypo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Keyword Extraction
Keyword extraction is tasked with the automatic identification of terms that best describe the subject of a document. ''Key phrases'', ''key terms'', ''key segments'' or just ''keywords'' are the terminology which is used for defining the terms that represent the most relevant information contained in the document. Although the terminology is different, function is the same: characterization of the topic discussed in a document. The task of keyword extraction is an important problem in text mining, information extraction, information retrieval and 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 pro ... (NLP). Keyword assignment vs. extraction Keyword assignment methods can be roughly divided into: * keyword assignment (keywords are chosen from controlled vocab ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
