Good day! Looking for an example or a demo which describe complete process of requirement change management using similar historic change request using any machine learning technique or any data mining technique. The main focus is to reuse previous change experience. To explain further, reffering text from a research paper.

Every time a new Request for a Change (RFC) comes in to the system, it is compared to changes stored in the Change Knowledge Base (CKB). An RFC represents the initial state of a change and the comparison occurs between the RFC at hand and the RFC of a past completed change, for the sake of simplicity, we will use the term change and RFC interchangeably. The CKB consists of the set of all changes performed in the past. The comparison of the RFC at hand with a particular change makes use of a similarity function that will be described in section 4. The most similar changes will be displayed to the user along with a measure (normalized to a value between 0 and 1) of how similar the change is to the RFC. A domain expert will provide feedback on whether or not they believe that the displayed changes are genuinely similar to the actual RFC.

Taken from research paper.http://ieeexplore.ieee.org/document/5488305/

Is this approach useful? If useful in which phase of requirement change management will it be useful?

From where can I get an example of complete process based on actual data ?

  • 1
    It’s best to include your existing knowledge on the topic to find useful answers. Have you already done any research about this topic? Which books, articles, websites, college class notes have you already searched? The question is too broad, the title can be a book name itself. :) – Gürkan Çetin Mar 10 '18 at 12:04
  • Maybe cross validated or data science stack exchange sites are better for answering this question ;). – Roberto Anzaldua Jul 2 '18 at 18:25

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