From: tatata9999@gmail.com   
      
   First, I'm an idiot, that is, I'm completely new to AI.  Here's a   
   problem I'm trying to solve:   
   a base text file that has about 5000 words (of 5 or 6k)   
   and   
   a small text file that has about 500 to 1000 words (of 0.5 to 1k,   
   about 10 to 20% of the bigger file)   
   I need to find how close the second/smaller file is to the bigger/base   
   file conceptually or semantically.   
      
   I understand there are a lot of praise about LSA or LSI for machine   
   learning of texts.  In the meantime, I'm thinking totally off my head   
   or you may call crazy to pose the following question, how difficult it   
   would be to extract 10 to 20 concepts or key meanings of the big file,   
   then figure out   
   what are the 3 to 5 Most Valuable Concepts (MVC) of the 10 or 20   
   concepts, and then, what's the author's view towards these MVCs,   
   hence, these concepts become contextual...  Well, it's slightly   
   easier, better, better accuracy with the smaller file, apply it the   
   smaller file then...   
      
   Am I out of my mind?   
      
   Thanks for your time.   
      
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