Text mining : vers un nouvel accord avec Elsevier | Sciences communes
La semaine est placée sous le signe de la divulgation de documents officiels sur le text mining (pourrait-on parler de MiningLeaks ?). Le collectif Savoirscom1 vient de publier le rapport du Conseil supérieur de la propriété littéraire et artistique sur « l’exploration de données ». De mon côté, j’apporte quelques informations sur l’accord conclu entre le consortium Couperin et Elsevier concernant la licence de data et text mining accordée par le géant de l’édition scientifique à plusieurs centaines d’établissements universitaires et hospitaliers français. Contre toute attente, les nouvelles sont meilleures du côté d’Elsevier que du CSPLA : en digne représentant des ayants-droits, le Conseil vient de retoquer toute éventualité d’exception au droit d’auteur pour les projets scientifiques de text mining (alors que le Royaume-Uni vient tout juste d’en voter une, et qu’il s’agit d’un des principaux axes des projets de réforme européens du droit d’auteur). Ce projet initial a été clarifié.
Text mining
A typical application is to scan a set of documents written in a natural language and either model the document set for predictive classification purposes or populate a database or search index with the information extracted. Text mining and text analytics[edit] The term text analytics describes a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for business intelligence, exploratory data analysis, research, or investigation.[1] The term is roughly synonymous with text mining; indeed, Ronen Feldman modified a 2000 description of "text mining"[2] in 2004 to describe "text analytics The term text analytics also describes that application of text analytics to respond to business problems, whether independently or in conjunction with query and analysis of fielded, numerical data. History[edit] Text analysis processes[edit] Subtasks — components of a larger text-analytics effort — typically include: Software[edit]
What is Data Mining? A Webopedia Definition
Main » TERM » D » By Vangie Beal Data mining requires a class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. For example, data mining software can help retail companies find customers with common interests. The phrase data mining is commonly misused to describe software that presents data in new ways. Data mining is popular in the science and mathematical fields but also is utilized increasingly by marketers trying to distill useful consumer data from Web sites.
List of text mining software
From Wikipedia, the free encyclopedia Text mining computer programs are available from many commercial and open source companies and sources. Commercial[edit] Commercial and Research[edit] RxNLP API for Text Mining and NLP – text mining APIs for both research and commercial use. Open source[edit] References[edit] External links[edit]
List of text mining software - Wikipedia
From Wikipedia, the free encyclopedia Text mining computer programs are available from many commercial and open source companies and sources.
Begin Text Mining - Text & Data Mining - InfoGuides at George Mason University
Get started with text mining (aka data mining, text analysis, or TDM) with these recommendations for: Best Practices: Strategies and steps to follow for text mining projects. Tutorials: Teach yourself text mining. Texts: Collections of texts (corpora). Software: Software and tools for use in text mining. Many of these are free! Help: Contact information for additional guidance. Text mining is useful for looking into major trends in a large number of documents.
Library Sources - Text Mining & Computational Text Analysis - Library Guides at UC Berkeley
Some datasets from the ICPSR include corpora assembled to support data analyses, and include sources such as survey text, text messages, the Congressional Record, political speeches and more. Consortium of 325 institutions working together to acquire and preserve social science data. Maintained at University of Michigan, ICPSR receives, processes, and distributes data on social phenomena in 130 countries. Includes survey data, census records, election returns, economic data, and legislative records.
Data for Research (dfr.jstor.org)
Data for Research (dfr.jstor.org) is a free, self-service tool that allows computer scientists, digital humanists, and other researchers to select and interact with content on JSTOR. Created in 2008, Data for Research enables exploration of both scholarly journal literature (more than 7 million journal articles) and a set of primary resources (26,000 19th Century British Pamphlets). The resource consists of a set of web-based tools, including: a powerful faceted search interface that can be leveraged to define content of interest through an iterative process of searching and results filtering word frequencies, citations, key terms, and ngrams utilized for conducting analysis of document-level data topic modeling (classification of subject headings at the article level), a powerful tool for content selection and filtering downloadable datasets containing word frequencies, citations, key terms, or ngrams associated with the content selected visualization tools
