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François Dongier

How Google Buzz is Disruptive: Open Data Standards - 0 views

www.readwriteweb.com/...uptive_open_data_standards.php

googlebuzz dataportability

shared by François Dongier on 10 Feb 10 - Cached
  • Under the covers, though, this major product was built by a team of people taking a radical new approach to online publishing: Buzz is all about open, standardized user data.
  • Google Buzz data can be syndicated out to other services using the standard data formats called Atom, Activity Streams, MediaRSS and PubSubHubbub.
  • a look at its APIs and developer roadmap indicate that it may actually intend to be a platform - the central hub for a world of distributed social networking.
  • ...7 more annotations...
  • if the growing number of data portability and open web advocates the company has hired can do their jobs well - then Google Buzz could be a big force for good.
  • People will build services on top of analyzing your public Buzz activity. They will build new applications for publishing to Buzz,
  • Planned support for things like the Salmon commenting standard mean that comments left on Buzz could appear out on blog posts around the web, and comments on blog posts could be viewed inside of Buzz when the post links are shared.
  • a cross-platform messaging service. Facebook users can only message other Facebook users
  • Is Google centralizing too much of the decision making about the future of an ostensibly decentralized web?
  • "Comin soon - Over the next several months Google Buzz will introduce an API for developers, including full/read write support for posts with the Atom Publishing Protocol, rich activity notification with Activity Streams, delegated authorization with OAuth, federated comments and activities with Salmon, distributed profile and contact information with WebFinger, and much, much more."
  • It would have been disruptive if google had pushed W3C standards for sharing data (Semantic web technologies, LinkedData, ...). But does Google really want to push semantic web technologies, making the web easier to search ?
François Dongier

10 Ways to Use OpenCalais Today | OpenCalais - 0 views

www.opencalais.com/...10-ways-use-opencalais-today

entity extraction opencalais openpublish

shared by François Dongier on 06 Feb 10 - Cached
  • What Does Calais Do?
  • It analyzes text you send it and extracts entities (people, organizations, geographies, etc.). In many cases, it links those entities to the world of Linked Data. It extracts facts – like the fact that John Doe is the CEO of Acme Corporation or such. It extracts events – like mergers, earning announcements, natural disasters and a bunch of others. It attaches a topic to the text as a whole, much like a newspaper would (Sports, Finance, Health, etc.). It creates SocialTags – our attempt to “tag” the article a way a human would to file it away somewhere.
  • it’s free for up to 50,000 submissions per day for commercial or non-commercial purposes
  • ...5 more annotations...
  • Content Enhancement — There’s a whole world of Linked Data out there and OpenCalais can be your entry point. For example – take in press releases, and extract the companies mentioned in them. Use OpenCalais’ Linked Data entry points to get the SIC codes and the link to DBPedia. Access DBPedia and enhance your content with other information about the company like locations, people, products. Access Geonames to figure out what region the company is located in. Take that enhanced content and do cool things (like triage and workflow and presentation) with it.
  • Alerting — Give users the ability to be alerted when certain types of content becomes available. Unlike simple keyword alerting with OpenCalais + Linked Data you can construct alerts like, “Tell me when there is M&A activity for a company in the Steel industry.”
  • Automated News Portals — Want to create a general purpose news portal? Or maybe one that deals only with baseball news? Great. Subscribe to and/or acquire some content sources, and feed them through OpenCalais. Then use the metadata to throw away what you don’t care about and to organize the rest by topic, geography, person – whatever. A great example of an off-the-shelf solution that does this is OpenPublish.
  • Finer-Grained / Higher-Value Syndication — Do you have content consumers via RSS or other syndication methods? Give them a better experience by allowing them to create their own channels based on OpenCalais metadata. Create channels based on region, types of events, companies, etc. – or any combination of those and other items.
  • SEO — Something we get asked about all the time – we know people are experimenting – but they’re not being very public about their experimentation. Here’s a simple idea though: make your content more search friendly. Two routes: One easy, one a little harder. Route 1: Translate events into human readable text and get it on your page. Have a complicated article about an LBO of company x by people y? OpenCalais will identify an M&A event. Take that event and turn it into a tag like “Acquisitions” – something people might actually search for. Don’t just use it as a metatag – incorporate into the page via navigation or whatever so Google pays attention. Route 2: Use linked data to enhance your content. If you’re talking about a company or geography use OpenCalais Linked Data to enhance the page with additional information from Dbpedia, Geonames, CIA world fact book or a bunch of other sources.
François Dongier

Extracting Enterprise Vocabularies Using Linked Open Data | Semantic Web Dog Food - 0 views

data.semanticweb.org/...html

linkeddata Juan Sequeda entity extraction vocabularies

shared by François Dongier on 04 Feb 10 - Cached
  • A common vocabulary is vital to smooth business operation, yet codifying and maintaining an enterprise vocabulary is an arduous, manual task. We describe a process to automatically extract a domain specific vocabulary (terms and types) from unstructured data in the enterprise guided by term definitions in Linked Open Data (LOD). We validate our techniques by applying them to the IT (Information Technology) domain, taking 58 Gartner analyst reports and using two specific LOD sources -- DBpedia and Freebase.
    • François Dongier
      François Dongier on 04 Feb 10
       
      This IBM article is referenced by Juan Sequeda in a post to the Linking Open Data mailing list (public-lod@w3.org, Feb 4, 2010) : Hi Matthias, We worked on something similar: entity type discovery using linked open data. Our project was given a corpus of documents in the same domain, identify specific entity types in the documents. Our objective was to search for documents in a corpus by specific entities. For example: "find articles that are about RDBMs" Standard NER tools identify high level types such as persons, organization, places because they have been previously trained on general corpora. I assume tools like OpenCalais have been trained on news-like documents and Zemanta has been trained on blog-like documents. We were interested in identifying specific types such a "RDBMS" when the word "Oracle" would show up in the text. In order to do that, we followed several domain term extraction techniques. We used LOD, specifically DBpedia, Freebase and Opencyc to disambiguate terms and also retrieve the entities. Honestly, evaluation is pretty hard to do, but our current implementation was not that bad (75% precision and 55% recall). We built upon some work by IBM where they create a vocabulary from text using LOD [1] Let me see if I can clean up the code and publish it as a service. [1] http://data.semanticweb.org/conference/iswc/2009/paper/inuse/143/html Juan Sequeda (575) SEQ-UEDA www.juansequeda.com
Kurt Laitner

Epiphany - 2 views

projects.dfki.uni-kl.de/epiphany

shared by Kurt Laitner on 04 Feb 10 - No Cached
Kurt Laitner

Parse.ly | personalized recommendations that connect you with the content you'll love - 1 views

www.parse.ly

parse.ly

shared by Kurt Laitner on 01 Feb 10 - Cached
  • François Dongier on 02 Feb 10
     
    Seems interesting. I think I'll give it a try. And they have an API. Not much info given about the machine learning algorithm at work, but looks like a nice attempt towards user-managed personalised recommendations. List your interests, state their importance (most, extremely, very, moderately, somewhat), rate the recommendations and let the algorithm do its magic and improve its recommendations over time.
  • François Dongier on 02 Feb 10
     
    I entered a set of interests and am now waiting for activation of my account (if someone has an invite, thanks)
François Dongier

Overview - parselyapi v0.1 documentation - 0 views

parse.ly/api

parselyapi

shared by François Dongier on 02 Feb 10 - Cached
  • For Techies and Mashup Authors: Want to tap into Parse.ly’s powerful real-time news and blog article processing infrastructure and recommendation algorithms for your own online mashup? Have a great idea for a mobile news iPhone/Android app, or an Adobe Air desktop notification system for real-time news updates? Parse.ly’s API gives you access to the best content the web has to offer – from over 120K sources – but also allows you to personalize the results based on individual user interests.
  • HTTP, REST and JSON
  • OAuth
  • ...2 more annotations...
  • RESTful APIs
  • JavaScript Object Notation (JSON)
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