title: Clustering Based-On Multi-Word Similarity
body: <p>I am trying to implement clustering for bank transaction data. The dataset contains columns about <code>Vendor</code> and <code>MCC</code> which are <code>string</code>. There are too much distinct values in those columns, I want to make a clustering depending on some metrics such as <code>cosine similarity</code> for <code>Vendor or MCC</code>. ( For example <code>'Hotel A'</code> and <code>'Hotel B'</code> can be in the same cluster. ) I think <code>Levenshtein distance</code> is not sufficient for this.</p>
  <p>I think about finding a corpus for MCC and create a model for find similarity between the words. Is this method good for this problem? If not, how can I handle with those columns? If yes, is there a corpus for this?</p>
  <p>Data source: <a href="https://data.world/oklahoma/purchase-card-fiscal-year" rel="nofollow noreferrer">https://data.world/oklahoma/purchase-card-fiscal-year</a></p>