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Match a two items from two different receipts



The Next CEO of Stack Overflow
2019 Community Moderator Electionsimilarity measure with two featuresMahalanobis distance between two clustersJaccard similarity between two itemsIs there a way to measure correlation between two similar datasets?Is there an algorithm or NN to match two documents, basically not closely similar?Finding similarity between two histogram plotsWhat is the efficient way to generate a similarity score when comparing two face images?Euclidean distance for more than two datapointsProximity distance between two stringscosine similarity between items (purchase data) and normalisation










0












$begingroup$


I have two different invoices or receipts. One is a Purchase order one is something like a receipt(acknowledgement).



Suppose I have ordered(PO) Wine:



  1. White Wine

  2. Red Wine

  3. Rose Wine

And I receive the acknowledgement as:



  1. Wine Red Jacobs Creek

  2. White Wine

  3. Winter's Hill Estate Dry Rose

I want to match the strings (items) in the Purchase Order and the Invoice.



Can you suggest me ways to do it.



I have tried vectorization using Count Vectorization Alg
Then have used distance measures to calculate similarity using:
'dice', 'rogerstanimoto', 'yule', 'hamming', 'jaccard', 'braycurtis', 'canberra', 'cityblock', 'correlation', 'cosine', 'euclidean', and 'minkowski'



The problem is the position of Words.



Red Wine is will not be similar to Wine Red. But that should not be the case.



I have tried Word2Vec Algorithm too but as this is not language technically just Nouns. It did not work.










share|improve this question











$endgroup$
















    0












    $begingroup$


    I have two different invoices or receipts. One is a Purchase order one is something like a receipt(acknowledgement).



    Suppose I have ordered(PO) Wine:



    1. White Wine

    2. Red Wine

    3. Rose Wine

    And I receive the acknowledgement as:



    1. Wine Red Jacobs Creek

    2. White Wine

    3. Winter's Hill Estate Dry Rose

    I want to match the strings (items) in the Purchase Order and the Invoice.



    Can you suggest me ways to do it.



    I have tried vectorization using Count Vectorization Alg
    Then have used distance measures to calculate similarity using:
    'dice', 'rogerstanimoto', 'yule', 'hamming', 'jaccard', 'braycurtis', 'canberra', 'cityblock', 'correlation', 'cosine', 'euclidean', and 'minkowski'



    The problem is the position of Words.



    Red Wine is will not be similar to Wine Red. But that should not be the case.



    I have tried Word2Vec Algorithm too but as this is not language technically just Nouns. It did not work.










    share|improve this question











    $endgroup$














      0












      0








      0


      2



      $begingroup$


      I have two different invoices or receipts. One is a Purchase order one is something like a receipt(acknowledgement).



      Suppose I have ordered(PO) Wine:



      1. White Wine

      2. Red Wine

      3. Rose Wine

      And I receive the acknowledgement as:



      1. Wine Red Jacobs Creek

      2. White Wine

      3. Winter's Hill Estate Dry Rose

      I want to match the strings (items) in the Purchase Order and the Invoice.



      Can you suggest me ways to do it.



      I have tried vectorization using Count Vectorization Alg
      Then have used distance measures to calculate similarity using:
      'dice', 'rogerstanimoto', 'yule', 'hamming', 'jaccard', 'braycurtis', 'canberra', 'cityblock', 'correlation', 'cosine', 'euclidean', and 'minkowski'



      The problem is the position of Words.



      Red Wine is will not be similar to Wine Red. But that should not be the case.



      I have tried Word2Vec Algorithm too but as this is not language technically just Nouns. It did not work.










      share|improve this question











      $endgroup$




      I have two different invoices or receipts. One is a Purchase order one is something like a receipt(acknowledgement).



      Suppose I have ordered(PO) Wine:



      1. White Wine

      2. Red Wine

      3. Rose Wine

      And I receive the acknowledgement as:



      1. Wine Red Jacobs Creek

      2. White Wine

      3. Winter's Hill Estate Dry Rose

      I want to match the strings (items) in the Purchase Order and the Invoice.



      Can you suggest me ways to do it.



      I have tried vectorization using Count Vectorization Alg
      Then have used distance measures to calculate similarity using:
      'dice', 'rogerstanimoto', 'yule', 'hamming', 'jaccard', 'braycurtis', 'canberra', 'cityblock', 'correlation', 'cosine', 'euclidean', and 'minkowski'



      The problem is the position of Words.



      Red Wine is will not be similar to Wine Red. But that should not be the case.



      I have tried Word2Vec Algorithm too but as this is not language technically just Nouns. It did not work.







      similarity distance text cosine-distance






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited 1 hour ago









      Anony-Mousse

      5,045625




      5,045625










      asked Feb 28 at 6:55









      Kavita AherwarKavita Aherwar

      11




      11




















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