GATE, NLTK: Basic components of Machine Learning (ML) System

Machine Learning Components

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 is Semantic 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 a Recommendation 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 GATE, Stanford NLP and OpenNLP .

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

In my subsequent blogs I will talk more in details.

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6 thoughts on “GATE, NLTK: Basic components of Machine Learning (ML) System

  1. tirumurugan (@bm07558)

    I understand NLP and POP, But I have doubt in semantic rule engine? IT means Using NLP you will get noun and numbers, then how can you write rule using those data? and how to collect >20 dollar phones?
    Advance thanks for your answer.

    Reply
    1. GoSmarter Post author

      Tiru, thanks for visiting my website and participating in the discussion. Did you mean POS (Parts of Speach analysis) not POP? Also for Semantic Rule Engine you typically use . In JAPE you define rules like “Greater than” “Less than” and it will extend it to the Rules using regular expression. Refer this blog for more information.

      Reply
  2. document

    Hi would you mind letting me know which hosting company you’re utilizing? I’ve loaded
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    Reply
  3. Pingback: Sample iPad app to work with JSon based Machine Learning System | GoSmarter Tech Blog

  4. nellaivijay

    Well written, you have described complex architecture in simplified way, looking for more article on this ML, NLP area from you…

    Reply

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