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François Dongier

Overview - parselyapi v0.1 documentation - 0 views

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
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  • RESTful APIs
  • JavaScript Object Notation (JSON)
François Dongier

10 Ways to Use OpenCalais Today | OpenCalais - 0 views

  • 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
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  • 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

Google Prediction API - Google Code - 0 views

  • What is the Google Prediction API? The Prediction API enables access to Google's machine learning algorithms to analyze your historic data and predict likely future outcomes. Upload your data to Google Storage for Developers, then use the Prediction API to make real-time decisions in your applications. The Prediction API implements supervised learning algorithms as a RESTful web service to let you leverage patterns in your data, providing more relevant information to your users. Run your predictions on Google's infrastructure and scale effortlessly as your data grows in size and complexity.
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