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Enterprise Architect in HCL Technologies a $7Billion IT services organization. My role is to work as a Technology Partner for large enterprise customers providing them low cost opensource solutions around Java, Spring and vFabric stack. I am also working on various projects involving, Cloud base solution, Mobile application and Business Analytics around Spring and vFabric space. Over 23 yrs, I have build repository of technologies and tools I liked and used extensively in my day to day work. In this blog, I am putting all these best practices and tools so that it will help the people who visit my website. Krishna is a DZone MVB and is not an employee of DZone and has posted 64 posts at DZone. You can read more from them at their website. View Full User Profile

GATE, NLTK: Basic Components of a Machine Learning System

02.13.2013
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I am currently building a Machine Learning system. In this blog I want to captures the elements of a machine learning system.

My definition of a Machine Learning System is to take voice or text inputs from a user and provide relevant information. And over a period of time, learn the user behavior and provides him better information.  Let us hold on to this comment and dissect apart each element.

In the below example, we will consider only text input. Let us also assume that the text input will be a freeflowing English text.

  • As a 1st step, when someone enters a freeflowing text, we need to understand what is the noun, what is the verb, what is the subject and what is the predicate. For doing this we need a Parts of Speech analyzer (POS), for example “I want a Phone”. One of the components of Natural Language Processing (NLP) is POS.
  • For associating relationship between a noun and a number, like “Phone greater than 20 dollers”, we need to run the sentence thru a rule engine. The terminology used for this isSemantic Rule Engine
  • The 3rd aspect is the Ontology, where in each noun needs to translate to a specific product or a place. For example, if someone says “I want a Bike” it should translate as “I want a Bicycle” and it should interpret that the company that manufacture a bicycle is BSA, or a Trac. We typically need to build a Product Ontology
  • Finally if you have buying pattern of a user and his friends in the system, we need aRecommendation Engine to give the user a proper recommendation

2 programming language which have good support of these capabilities are Python and Java. Python has a framework called Natural Language Tool Kit (NLTK). To understand more about NLTK, please refer the Cookbook. Java has a framework called GATEStanford NLP andOpenNLP .

For this discussion, we will consider GATE and related frameworks.

In my subsequent blogs I will talk more in details.

Published at DZone with permission of Krishna Prasad, author and DZone MVB. (source)

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