Web personalization and personalized recommendations are recently gaining more and more interest. Companies like Amazon, Google, Netflix, The New York Times, Facebook, Twitter, … already personalize their products in different ways. If you take Google’s search results as an example. Have you ever noticed that a friend of you gets different search results as you do for the same search query? If you never have noticed just try it out it’s really worth noting. Another example are Amazon’s product recommendations which are for example based on your purchases, your product ratings and so on.
Eli Pariser explains in the following TED Talk how “human information filters” get substituted by algorithmic ones, which means how recommendation engines filter information for you. Have a look at the video is is really worth watching:
Do you know other examples of web personalization or recommendations engines? Please leave me a comment at the end of this post.
Grabeeter enables you to grab your tweets which means that you are able to store your tweets on your local harddrive in a structured format (xml at the time). Using the Grabeeter Client you are also able to perform searches on your local stored tweets.
This solves in parts the following problem. Maybe some of you have already noticed that if you have written more than 3200 Tweets you are not able to access your first tweets anymore due to Twitter access restrictions.
If you register on Grabeeter before you have reached the 3200 Tweets on Twitter you are able to access all your written tweets in the future. Grabeeter archives your tweets and enables you to export them in a structured format (XML and JSON at the time). You can also use Grabeeter Client to directly access your interesting tweets on Twitter again.
Just go to Grabeeter and register with your twitter username. All the other work is done for you. You can afterwards export and search your tweets online or using Grabeeter Client offline.
For all developers we also provide a small Grabeeter API in order to access your tweets using an application you developed.
Have fun and we are happy to get feedback from you.
Kevin Weil, Analytics Lead at Twitter recently gave a presentation on Twitter’s use of Cassandra, Pig and HBase. Specially interesting is how Twitter uses Hadoop and Pig in their data analysis process.