Connaissances & classifications du Monde du Classement Une représentation synthétique des connaissances sous forme de classifications pour assimiler, mémoriser ou communiquer un concept. Actualité Aide Contenu du site Vous pouvez consultez les informations sur ce projet et les liens. Knowledge tags The use of keywords as part of an identification and classification system long predates computers. Paper data storage devices, notably edge-notched cards, that permitted classification and sorting by multiple criteria were already in use prior to the twentieth century, and faceted classification has been used by libraries since the 1930s. Online databases and early websites deployed keyword tags as a way for publishers to help users find content. In the early days of the World Wide Web, the keywords meta element was used by web designers to tell web search engines what the web page was about, but these keywords were only visible in a web page's source code and were not modifiable by users. "A Description of the Equator and Some ØtherLands", collaborative hypercinema portal, produced by documenta X, 1997.
Firewall Builder | Quick Start Guide This short guide provides the basic information new users need to save time when first learning to use the Firewall Builder application. The complete Firewall Builder Users Guide can be found here. Key Concepts Objects. Firewall Builder is based on the concept of objects. GUI Layout The Firewall Builder application is comprised of three primary panels shown in the screenshot below. Object Panel. Panels open dynamically based on what activity the user is performing. Creating a New Firewall To create a new firewall object, click on the Create New Firewall shortcut in the center of the screen. Platform. Hint: You can also create a new firewall by clicking on the New Object icon at the top of the Object Panel and selecting New Firewall. Configuring Rules Before you can use an object in a firewall rule it must first exist in an object Library. The diagram below shows the location of buttons for many common actions. Create New Objects. Compiling and Installing Rules Deployment is done in 2 steps:
Article : diff entre Taxonomie, Thésaurus, etc. (This excellent overview was written by Woody Pidcock of the Boeing company and posted at metamodel.com. It has been edited slightly so it could be archived here.) I will answer this question one step at a time. To keep this answer focused on the question, I will use other concepts that I will not define here. A controlled vocabulary is a list of terms that have been enumerated explicitly. If the same term is commonly used to mean different concepts in different contexts, then its name is explicitly qualified to resolve this ambiguity. A taxonomy is a collection of controlled vocabulary terms organized into a hierarchical structure. A thesaurus is a networked collection of controlled vocabulary terms. People use the word ontology to mean different things, e.g. glossaries & data dictionaries, thesauri & taxonomies, schemas & data models, and formal ontologies & inference. People make commitments to use a specific controlled vocabulary or ontology for a domain of interest. Additions ¶
The Accidental Taxonomist: Taxonomy Trends and Future What are the trends in taxonomies, and where is the field going? The future of taxonomies turned out to be a unifying theme of last week’s annual Taxonomy Boot Camp conference, in Washington, DC, the premier event in taxonomies, from its opening keynote to its closing panel. “From Cataloguer to Designer” was the title of the opening keynote, an excellent presentation by consultant Patrick Lambe of Straits Knowledge. He said that there are new opportunities for taxonomists, especially in the technology space, if they change their mindset and their role from that of cataloguers, who describe the world as it is, to that of designers, who plan things as they could be. The spread of greater understanding of taxonomies was a common theme of that panel. Looking to the future, the panelists’ shared predictions included greater use of linked data, taxonomy visualization, and text analytics. New trends and technologies were discussed in individual presentations, too.
User's Guide to the Internet A User’s Guide to the Internet was compiled by Vivian Hutchison, an ALIC student library technician from the College of Information Science at the University of Maryland. History of the Internet History of Weblogs This article from Wired discusses the history of blogs and the outlook for the future. Hobbes’ Internet Timeline A history of the Internet through a timeline design and various links to further information. Internet Archive Archives web pages back to 1996 and includes special collections dating back to 1903. The Evolution and Revolution of Search Engines This site discusses the evolution of search engines. Top of Page Internet Tutorials Bare Bones 101: A Basic Tutorial on Searching the Web University of South Carolina The information contained in this site is designed to get users started in the right direction with a minimum amount of time and effort. Choose the Best Search for Your Information Need Finding Information on the Internet: A Tutorial Internet 101: Beginner’s Handbook Melissa S.
TermSciences - Terminologie Scientifique Knowledge retrieval Knowledge Retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items. It draws on a range of fields including epistemology (theory of knowledge), cognitive psychology, cognitive neuroscience, logic and inference, machine learning and knowledge discovery, linguistics, and information technology. Overview In the field of retrieval systems, established approaches include: Data Retrieval Systems (DRS), such as database management systems, are well suitable for the storage and retrieval of structured data.Information Retrieval Systems (IRS), such as web search engines, are very effective in finding the relevant documents or web pages. Both approaches require a user to read and analyze often long lists of data sets or documents in order to extract meaning. The goal of knowledge retrieval systems is to reduce the burden of those processes by improved search and representation. References