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4. Searching and Ranking > Learning from Clicks

Learning from Clicks

One of the major advantages of online applications is that they receive constant feedback in the form of user behavior. In the case of a search engine, each user will immediately provide information about how much he likes the results for a given search by clicking on one result and choosing not to click on the others. This section will look at a way to record when a user clicks on a result after a query, and how that record can be used to improve the rankings of the results.

To do this, you’re going to build an artificial neural network that you’ll train by giving it the words in the query, the search results presented to the user, and what the user decided to click. Once the network has been trained with many different queries, you can use it to change the ordering of the search results to better reflect what users actually clicked on in the past.


  

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