{"id":2360,"date":"2017-06-11T15:02:24","date_gmt":"2017-06-11T13:02:24","guid":{"rendered":"https:\/\/blog.mi.hdm-stuttgart.de\/?p=2360"},"modified":"2023-08-06T21:50:42","modified_gmt":"2023-08-06T19:50:42","slug":"analyzing-text-with-ibm-watson-services-on-bluemix","status":"publish","type":"post","link":"https:\/\/blog.mi.hdm-stuttgart.de\/index.php\/2017\/06\/11\/analyzing-text-with-ibm-watson-services-on-bluemix\/","title":{"rendered":"Analyzing text with IBM Watson services on Bluemix"},"content":{"rendered":"

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You might have already heard of IBM’s artificial intelligence “Watson”, which beat two former champions  of the american television game show “Jeopardy!”<\/em><\/a>  back in 2011. What you probably don’t know is that today lots of predefined Watson services are publicy available on IBM’s cloud platform “Bluemix”. These services cover different aspects of AI-backed applications like Visual Recognition, Language Translation or Text to Speech. This post glances on Natural Language Understanding, which is about analyzing text by extracting different kinds of information, and shows how this can be achieved by using Bluemix services.<\/p>\n

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Requirements<\/h2>\n

Before we can get started playing around with Watson, we must make sure to have a valid Bluemix account available. If you don’t already have a Bluemix acoount, head for the IBM Bluemix homepage<\/a> and get a 30-day trial for free. That’s it, now we’re ready to get started.<\/p>\n

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Launching a Watson service on Bluemix<\/h2>\n

From your Bluemix console, go to Catalog > Services > Watson, <\/em>which should give you a list of currently available Watson services. The service we’ll use for our test analysis example is Natural Language Understanding (NLU)<\/strong>. Once we have this service up and running, we’ll pass it the URL of a previous blog post and make it examine the post for keywords, categories and metadata.
\nSelecting the service in the list brings us to another page where we can choose a name as well as a plan for our service. Select the free plan (which limits the amount of operations you can execute per day and won’t cost you anything) and  click the “Create” button. After a short amount of time, your Watson service should be displayed on your Bluemix Dashboard and is therefore ready to do some work.
\nAfter making sure that your service has started, open it in the Dashboard. Among other things, this page shows the credentials (username\/password) you’ll need for authentication and also the base URL for talking to the previously created service. Since we’ll need this information repeatedly throughout the rest of this tutorial, make sure you keep this page open.<\/p>\n

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Testing our Watson service<\/h2>\n

To find out what the Watson NLU service can do, select your service on the Bluemix Dashboard (if you haven’t already) and click Manage <\/em>in the left-side panel. The management page provides you with a rough overview and refers to the Documentation<\/em> for further information.
\nThis should open the Watson Developer cloud<\/em> page, which offers detailed information on how to create Watson services (what we just did), how to use the NLU API and much more. Feel free to look around and examine the docs on your own.
\nIn order to interact with our newly created Watson service, we’ll make use of its RESTful HTTP interface. I’ll use the Postman <\/em>REST client for the rest of this tutorial. As an alternative, consider using the API explorer <\/em>which can be accessed from the documentation start page. This tools allows you to interactively compose and send HTTP requests by means of a very nice GUI. If you prefer working with the command line, there’re also examples of how to do it with cURL.
\nAs a test scenario, let’s assume we have a blog post and we want to get a rough overview by extracting and skimming the most significant keywords which capture the essence of the post. For demo purposes, I will feed one of my former posts on Docker Security<\/a> to the NLU service. Feel free to choose any other article for your own experiments.
\nThe Watson API allows us to pass text by either provide a public URL or directly embedding it into an HTTP request. I decided to pass the post by URL, since it can be generally accessed via the internet and is a much less verbose method than copying and pasting the whole text. Beyond sending the data to work with, we also have to specify what we want our service to do with the article (extract keywords and metadata).
\nAll in all, we send the following parameters along with our request:<\/p>\n