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courses:rg:2013:composite-activities [2013/04/23 18:06]
machys 		courses:rg:2013:composite-activities [2013/09/29 21:35] (current)
machys
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       * Do you have any idea how to do it differently?       * Do you have any idea how to do it differently?
    - Experiments: Which "tricks"/"parts of processing" enhanced the //Attribute recognition// and //Composite activity classification// tasks "the most"? Try to answer why.    - Experiments: Which "tricks"/"parts of processing" enhanced the //Attribute recognition// and //Composite activity classification// tasks "the most"? Try to answer why.
 +
 +====== Answers ======
 +
 +   - First set
 +      * list components [[https://docs.google.com/drawings/d/12wIoIDVDV3b6EbJAVVIzZn9h0ymIgHRHi_sTauGM08A/edit|(Google doc graph)]]
 +      * dependance of components (the same graph)
 +   - Scripts
 +      * reason?: Cheap source of training data, Many combinations, unseen variants, “decsriptions” of the same thing
 +      * four ways: 2x2: 1) direct use of words from data or 2) mapping word classes from WordNet X 3) simple word frequency or 4) TF*IDF
 +   - There was a discussion about 3rd set of question. We are not sure why authors do that. There was strongly supported opinion that autohors do a lot unnecessary work, which is lost by binarization.
 +   - 4th: Majority people in aswers nominated the use of TF*IDF in case of no training data as the best idea.
  

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