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DBpédia en français

DBpédia en français

Improving Decisions About Health, Wealth, and Happiness GoodRelations - GoodRelations is a lightweight ontology for annotating offerings and other aspects of e-commerce on the Web. GoodRelations is the only OWL DL ontology officially supported by both Google and Yahoo. It provides a standard vocabulary for expressing things like that a particular Web site describes an offer to sell cellphones of a certain make and model at a certain price, that a pianohouse offers maintenance for pianos that weigh less than 150 kg, or that a car rental company leases out cars of a certain make and model from a particular set of branches across the country. Also, most if not all commercial and functional details of e-commerce scenarios can be expressed, e.g. eligible countries, payment and delivery options, quantity discounts, opening hours, etc. The GoodRelations ontology is available under the Creative Commons Attribution 3.0 license. <?

Masters of Networks 2: Algorithmic detection of specialization in online conversations - Insite This is a writeup of the Team 1 hackathon at Masters of Networks 2. Participants were: Benjamin Renoust, Khatuna Sandroshvili, Luca Mearelli, Federico Bo, Gaia Marcus, Kei Kreutler, Jonne Catshoek and myself. I promise you it was great fun! The goal We would like to learn whether groups of users in Edgeryders are self-organizing in specialized conversations, in which (a) people gravitate towards one or two topics, rather than spreading their participation effort across all topics, and (b) the people that gravitate towards a certain topic also gravitate towards each other. Why is this relevant? Understanding social network dynamics and learning to see the pattern of their infrastructure can become a useful tool for policy makers to rethink the way policies are developed and implemented. Compared to traditional models of policy development, this method can allow for more effective and accountable policy interventions. The data The conversation was hosted on a Drupal 6 platform. What we did 1.

Linked Data | Linked Data - Connect Distributed Data across the Web Masters of Networks 2: what we will do - Insite Masters of Networks is essentially a hackathon. There will be no talks except a very short introduction by me. While hackathons typically organize themselves given good wi-fi and enough caffeine, we thought we would give it a modicum of structure. It works like this: There will be two teams. Team 1 – Algorithmic detection of specialization in online conversations What we do: we prototype a method for detecting emergent groups of “citizen specialists” in online consultations; people that bootstrap each other into a sort of informal high-level working group.This is relevant because: emergent specialization is likely to increase the firepower of the citizens collective intelligence in online consultation. Team 2 – Patterns in research funding in Italy How it works You show up at 10.00. What if I am not allocated to any team? We build teams just to save time. Do you guys have a hashtag? Sure! Sounds awesome! We still have one or two places.

Welcome to Apache™ Hadoop®! Watson (intelligence artificielle) Un prototype initial de Watson en 2011. Watson est un programme informatique d'intelligence artificielle conçu par la société IBM dans le but de répondre à des questions formulées en langage naturel[1]. Il s'intègre dans un programme de développement plus vaste, le DeepQA research project. Le nom « Watson » fait référence à Thomas J. En 2011, Watson connaît une notoriété au niveau mondial quand il devient le champion du jeu télévisé américain Jeopardy! Quatorze ans après la confrontation entre Deep Blue et le champion d'échecs Garry Kasparov, qui avait vu la défaite de ce dernier[4], les équipes d'IBM font participer Watson au célèbre jeu télévisé américain Jeopardy! À l'issue de trois manches diffusées les 14, 15 et 16 février 2011, Watson remporte le jeu télévisé face à Ken Jennings et Brad Rutter (en), deux des plus grands champions du jeu. Lors d'une session de répétition en condition de jeu réelle tenue mi-janvier 2011, Watson avait déjà gagné face aux deux champions[6].

Libby Miller's homepage Libby Miller's homepage Photo by Max Froumentin Since Jan 2005 I've been working for Asemantics - my mail address is though I'm still reachable on my bristol address. I was previously a senior technical researcher at the ILRT at the University of Bristol in the UK, working mostly on RDF, mostly in server-side Java or maybe a little light Perl, javascript, applescript or python. I want to catalogue the photos I took with my Palm camera and now my much better digital camera (you'll probably need Firefox for that link). Contact Find me on #rdfig and #foaf, or email. Work AsemanticsILRT Semantic Web papers, ILRT Semantic Web group page. foaf I'm a co-conspirator on foaf and RDFweb with Dan Brickley my foaf file, codepiction photo searching demo. (Old) Demos summary page

Outcomes, Impacts, and Indicators The Impact Survey was first used in 2009 to help gather data for the Opportunity for All study reports, conducted by the University of Washington’s iSchool with assistance from the Bill & Melinda Gates Foundation. Libraries were enlisted to connect to a web survey, the results of which were used to augment responses gathered through a telephone-based poll. To our surprise and delight, we gathered more than 45,000 survey responses in just ten weeks, with about 400 libraries participating. Even more delightful was finding that libraries were using the data from Opportunity for All as well as the reports of Impact Survey results from their own ­communities. Now, six years and several versions later, the Impact Survey is still showing the value of public access technology in libraries, and more libraries than ever are taking advantage of having outcomes, impacts, and indicators ready to measure with just a little bit of copying and pasting. Demonstrating what we do The language of evaluation

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Wikipedia structuré avec les technologies du web sémantique. by mbadion Feb 16