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In a narrower sense, language resource is specifically applied to resources that are available in digital form, and then, "encompassing (a) data sets (textual, multimodal/multimedia and lexical data, grammars, language models, etc.) in machine readable form, and (b) tools/technologies/services used for their processing and management". [1]
Language resource management – Lexical markup framework (LMF; ISO 24613), produced by ISO/TC 37, is the ISO standard for natural language processing (NLP) and machine-readable dictionary (MRD) lexicons. [1] The scope is standardization of principles and methods relating to language resources in the contexts of multilingual communication.
The lexical approach refers to various methods of teaching foreign languages with focus on lexical units of various sizes. On the smaller end, the lexical approach refers to teaching practices where vocabulary learning sets the preliminary ground for further language learning.
In computer programming, resource management refers to techniques for managing resources (components with limited availability).. Computer programs may manage their own resources [which?] by using features exposed by programming languages (Elder, Jackson & Liblit (2008) is a survey article contrasting different approaches), or may elect to manage them by a host – an operating system or ...
UBY-LMF [3] [4] is a format for standardizing lexical resources for Natural Language Processing (NLP). [5] UBY-LMF conforms to the ISO standard for lexicons: LMF, designed within the ISO-TC37, and constitutes a so-called serialization of this abstract standard. [6]
A rendition of the Vauquois triangle, illustrating the various approaches to the design of machine translation systems.. The direct, transfer-based machine translation and interlingual machine translation methods of machine translation all belong to RBMT but differ in the depth of analysis of the source language and the extent to which they attempt to reach a language-independent ...
A strong focus at UKP Lab is on utilizing novel natural language processing algorithms in real-life applications. UKP Lab collaborates with partners from academia and industry to improve various application scenarios, such as customer relationship management, digital humanities, educational applications, or public security.
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 ...