|
Word Sense Induction
In computational linguistics, word-sense induction (WSI) or discrimination is an open problem of natural language processing, which concerns the automatic identification of the senses of a word (i.e. meanings). Given that the output of word-sense induction is a set of senses for the target word (sense inventory), this task is strictly related to that of word-sense disambiguation (WSD), which relies on a predefined sense inventory and aims to solve the ambiguity of words in context. Approaches and methods The output of a word-sense induction algorithm is a clustering of contexts in which the target word occurs or a clustering of words related to the target word. Three main methods have been proposed in the literature: * Context clustering * Word clustering * Co-occurrence graphs Context clustering The underlying hypothesis of this approach is that, words are semantically similar if they appear in similar documents, with in similar context windows, or in similar syntactic cont ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Linguistics
Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others. Computational linguistics is closely related to mathematical linguistics. Origins The field overlapped with artificial intelligence since the efforts in the United States in the 1950s to use computers to automatically translate texts from foreign languages, particularly Russian scientific journals, into English. Since rule-based approaches were able to make arithmetic (systematic) calculations much faster and more accurately than humans, it was expected that lexicon, morphology, syntax and semantics can be learned using explicit rules, a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cluster Analysis
Cluster analysis or clustering is the data analyzing technique in which task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more Similarity measure, similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistics, statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis refers to a family of algorithms and tasks rather than one specific algorithm. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small Distance function, distances between cluster members, dense areas of the data space, intervals or pa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantics
Semantics is the study of linguistic Meaning (philosophy), meaning. It examines what meaning is, how words get their meaning, and how the meaning of a complex expression depends on its parts. Part of this process involves the distinction between sense and reference. Sense is given by the ideas and concepts associated with an expression while reference is the object to which an expression points. Semantics contrasts with syntax, which studies the rules that dictate how to create grammatically correct sentences, and pragmatics, which investigates how people use language in communication. Lexical semantics is the branch of semantics that studies word meaning. It examines whether words have one or several meanings and in what lexical relations they stand to one another. Phrasal semantics studies the meaning of sentences by exploring the phenomenon of compositionality or how new meanings can be created by arranging words. Formal semantics (natural language), Formal semantics relies o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Linguistics
Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others. Computational linguistics is closely related to mathematical linguistics. Origins The field overlapped with artificial intelligence since the efforts in the United States in the 1950s to use computers to automatically translate texts from foreign languages, particularly Russian scientific journals, into English. Since rule-based approaches were able to make arithmetic (systematic) calculations much faster and more accurately than humans, it was expected that lexicon, morphology, syntax and semantics can be learned using explicit rules, a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence. It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics. Major tasks in natural language processing are speech recognition, text classification, natural-language understanding, 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, though at the time that was not articulated as a problem separate from artificial intelligence. The proposed test includes a task that involves the automated interpretation and generation of natural language ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Polysemy
Polysemy ( or ; ) is the capacity for a Sign (semiotics), sign (e.g. a symbol, morpheme, word, or phrase) to have multiple related meanings. For example, a word can have several word senses. Polysemy is distinct from ''monosemy'', where a word has a single meaning. Polysemy is distinct from homonymy—or homophone, homophony—which is an Accident (philosophy), accidental similarity between two or more words (such as ''bear'' the animal, and the verb wikt:bear#Etymology 2, ''bear''); whereas homonymy is a mere linguistic coincidence, polysemy is not. In discerning whether a given set of meanings represent polysemy or homonymy, it is often necessary to look at the history of the word to see whether the two meanings are historically related. Lexicography, Dictionary writers often list polysemes (words or phrases with different, but related, senses) in the same entry (that is, under the same headword) and enter homonyms as separate headwords (usually with a numbering convention such ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Grammar Induction
Grammar induction (or grammatical inference) is the process in machine learning of learning a formal grammar (usually as a collection of ''re-write rules'' or '' productions'' or alternatively as a finite-state machine or automaton of some kind) from a set of observations, thus constructing a model which accounts for the characteristics of the observed objects. More generally, grammatical inference is that branch of machine learning where the instance space consists of discrete combinatorial objects such as strings, trees and graphs. Grammar classes Grammatical inference has often been very focused on the problem of learning finite-state machines of various types (see the article Induction of regular languages for details on these approaches), since there have been efficient algorithms for this problem since the 1980s. Since the beginning of the century, these approaches have been extended to the problem of inference of context-free grammars and richer formalisms, such as mult ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Word Sense Disambiguation
Word-sense disambiguation is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious. Given that natural language requires reflection of neurological reality, as shaped by the abilities provided by the brain's neural networks, computer science has had a long-term challenge in developing the ability in computers to do natural language processing and machine learning. Many techniques have been researched, including dictionary-based methods that use the knowledge encoded in lexical resources, supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, and completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date. Accuracy of current algorithms is dif ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
WordNet
WordNet is a lexical database of semantic relations between words that links words into semantic relations including synonyms, hyponyms, and meronyms. The synonyms are grouped into ''synsets'' with short definitions and usage examples. It can thus be seen as a combination and extension of a dictionary and thesaurus. Its primary use is in automatic natural language processing, text analysis and artificial intelligence applications. It was first created in the English language and the English WordNet database and software tools have been released under a BSD License, BSD style license and are freely available for download. The latest official release from Princeton was released in 2011. Princeton currently has no plans to release any new versions due to staffing and funding issues. New versions are still being released annually through the Open English WordNet website. Until about 2024 an online version was previously available through wordnet.princeton.edu. That version of WordNet h ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lexical Resource
In digital lexicography, natural language processing, and digital humanities, a lexical resource is a language resource consisting of data regarding the lexemes of the lexicon of one or more languages e.g., in the form of a database. Characteristics Different standards for the machine-readable edition of lexical resources exist, e.g., Lexical Markup Framework (LMF) an ISO standard for encoding lexical resources, comprising an abstract data model and an XML serialization, and OntoLex-Lemon, an RDF vocabulary for publishing lexical resources as knowledge graphs on the web, e.g., as Linguistic Linked Open Data. Depending on the type of languages that are addressed, a lexical resource may be qualified as monolingual, bilingual or multilingual. For bilingual and multilingual lexical resources, the words may be connected or not connected from one language to another. When connected, the equivalence from a language to another is performed through a bilingual link (for bilingual le ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Yahoo! Search
Yahoo! Search is a search engine owned and operated by Yahoo!, using Microsoft Bing to power results. Originally, "Yahoo! Search" referred to a Yahoo!-provided interface that sent Web search query, queries to a searchable index of pages supplemented with its directory of websites. The results were presented to the user under the Yahoo! brand. The actual Web crawler, web crawling and Data warehouse, data housing was not done by Yahoo! itself – in 2001, the searchable index was powered by Inktomi (company), Inktomi and later by Google until 2004, when Yahoo! built its own crawler, becoming independent. On July 29, 2009, Microsoft and Yahoo! announced a deal in which Bing would henceforth power Yahoo! Search, putting an end to Yahoo!'s in-house crawler. For four years between 2015 until the end of 2018, it was powered by Google, before returning to Microsoft Bing again. As of July 2018, Microsoft Sites handled 24.2 percent of all desktop search queries in the United States. Du ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graph (computer Science)
In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from the field of graph theory within mathematics. A graph data structure consists of a finite (and possibly mutable) set of ''vertices'' (also called ''nodes'' or ''points''), together with a set of unordered pairs of these vertices for an undirected graph or a set of ordered pairs for a directed graph. These pairs are known as ''edges'' (also called ''links'' or ''lines''), and for a directed graph are also known as ''edges'' but also sometimes ''arrows'' or ''arcs''. The vertices may be part of the graph structure, or may be external entities represented by integer indices or references. A graph data structure may also associate to each edge some ''edge value'', such as a symbolic label or a numeric attribute (cost, capacity, length, etc.). Operations The basic operations provided by a graph data structure ''G'' usually include:See, e.g. , Sec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
