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Visualizzazione dei post da Maggio, 2011


Sneakernet is a term used to describe the physical transfer of electronic information, especially computer files. The name is a tongue-in-cheek reference to sneakers, as this way of moving information relies on a courier and removable media such as USB drive and compact discs. Source: Osama bin Laden’s use of Technology, GeekwithLaptop

Online term extractors: Terminology Extraction by Translated

Terminology Extraction by Translate d uses Poisson statistics, the Maximum Likelihood Estimation and Inverse Document Frequency between the frequency of words in a given document and a generic corpus of 100 million words per language. It uses a probabilistic part of speech tagger to take into account the probability that a particular sequence could be a term. It creates n-grams of words by minimizing the relative entropy. Terminology Extraction by Translated can be also used to improve search results in traditional search engines (es. Google) by giving a better estimation of how much a keyword is relevant to a document. Texts may only be submitted for analysis through entering the text to analyze into the text window. Languages supported: English, Italian, French. Website: Translated

Online term extractors: AlchemyAPI

AlchemyAPI extracts topic keywords from HTML, text, or web-based content. AlchemyAPI employes sophisticated statistical algorithms and natural language processing technology to analyze data, extracting keywords that can be utilized to index content, generate tag clouds, and more. API endpoints are provided for performing keyword extraction on Internet-accessible URLs and posted HTML files or text content. Extracted meta-data may be returned in XML, JSON, RDF, and Microformats rel-tag formats. Keyword extraction is supported in over a half-dozen different languages, enabling even foreign-language content to be categorized and tagged: English, French, German, Italian, Portuguese, Russian, Spanish, Swedish. Website: AlchemyAPI

Online term extractors: TerMine

Particularly suitable for bio medical-area. Technical terms are important for knowledge mining, especially in the bio-medical area where vast amount of documents are available. The amount of terms (e.g., names of genes, proteins, chemical compounds, drugs, organisms, etc) is increasing at an astounding rate in the bio-medical literature. Existing terminological resources and scientific databases cannot keep up-to-date with the growth of neologisms. A domain independent method for term recognition is very useful to automatically Texts may be submitted for analysis through any of the following ways: entering the text you would like to analyze in to the topmost text window; specifying a text file (*.txt or *.pdf) from your computer's hard drive; entering a URL of the Web resource (*.html or *.pdf. Languages supported: all Unicode-compliant languages. Website: TerMine

Online term extractors: Maui - indexer

Maui automatically identifies main topics in text documents. Depending on the task, topics are tags, keywords, keyphrases, vocabulary terms, descriptors, index terms or titles of Wikipedia articles. This demo shows how a vocabulary can be used to derive the topics, e.g. High Energy Physics thesaurus or the agricultural thesaurus Agrovoc. It also shows how keyphrases can be extracted from document text. File formats supported: text, PDF, Microsoft Word file Website: Maui - indexer

Online term extractors: fivefilters

This is a free software project to enable easy term extraction through a web service. Given some text it will return a list of terms with (hopefully) the most relevant first. The list is returned in JSON format. It is a free alternative to Yahoo's Term Extraction service. It is being developed as part of the Five Filters project to promote alternative, non-corporate media. Languages supported: English Website: fivefilters

Online term extractors: Vocab Grabber

VocabGrabber analyzes any text you're interested in, generating lists of the most useful vocabulary words and showing you how those words are used in context. Just copy text from a document and paste it into the box, and then click on the "Grab Vocabulary!" button . VocabGrabber will automatically create a list of vocabulary from your text, which you can then sort, filter, and save. Select any word on the list and you'll see a snapshot of the Visual Thesaurus map and definitions for that word, along with examples of the word in your text. Languages supported: English. Website: Vocab Grabber

How to be a certified Terminology Manager

Striving for improving is for me a healthy way to add value and enjoy what I am doing. That's why I decided to get the ECQA certification in Terminology Management. This certification is a a good investment because it can be regarded as specialised professional qualification. The course comprises 6 units (5 theoretical units and 1 practical unit based on an exercise). For every unit participants will receive:  - A set of materials (to be found in a Moodle-based e-learning platform)  - An online tutorial (in form of a live webinar)  - And a discussion forum for questions and answers. UNIT 1: UNDERSTANDING TERMINOLOGY MANAGEMENT What is terminology? Why terminology management? How terminology work is embedded in my organisation and work environment? UNIT 2: TERMINOLOGY MANAGEMENT SKILLS How to search and collect terminology? How to store and retrieve? How to coin terms? How to manage monolingual and multilingual terminology? How to manage t