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So, after you've developed this elegant database schema around your data, what else can you do with it Remember when I was spouting off about "emergent properties" of systems in the Introduction A database schema based on the idea of partial decomposition can also exhibit emergent properties, developing smarts beyond the original design A good example of this is in the field of suggestions The complex maps you've built in the review_movie, review_review, and review_person tables can be even more useful, especially if you're interested in making suggestions to users, that is, providing information they might be interested in based on what they're looking at now The science of suggesting relevant information is nothing new Many software systems do this through methods such as collaborative filtering or lexical analysis The idea behind lexical analysis systems is to break documents down to their lexical components ords or phrases nd compare new documents based on a statistical relevance ranking of these components In theory, documents that have similar subject matter should rank closely together; in reality, lexical analysis often groups documents that don't necessarily go together For instance, lexical engines can readily group all of Shakespeare's works together, but a lexical system can't differentiate between a comedy and a tragedy If you were reading Troilus and Cressida and you wanted the system to show you "more plays like this one," it probably could manage to rule out Speed the Plow, but you might just as easily be shown As You Like It as Romeo and Juliet The system needs more information than purely lexical similarity to guide it Likewise, collaborative filtering, when left to its own devices, can develop strange behaviors Collaborative filtering attempts to suggest items to you based on matching your own likes and dislikes against all other users on the system Collaborative filtering's answer to the previous user request involves a complex equation based on what other readers who had read Troilus and Cressida had read and enjoyed This means that you might get a list of other Shakespearean tragedies as well.

<h1>All users</h1> <%= will_paginate %> <ul class="users"> <%= render @users %> </ul> <%= will_paginate %>

27 27 27 27 27

Here Rails infers that @users is an list of User objects; moreover, when called with a collection of users, Rails automatically iterates through them and renders each one with the _userhtmlerb partial The result is the impressively compact code in Listing 1033

Now that the user index is complete, there s only one canonical REST action left: destroy In this section, we ll add links to delete users, as mocked up in Figure 1012, and define the destroy action necessary to accomplish the deletion But first, we ll create the class of administrative users authorized to do so

15:14 15:13 15:14 15:14 15:14

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We will identify privileged administrative users with a boolean admin attribute in the User model, which will lead to an admin method to test for admin status We can write tests for this attribute as in Listing 1034

This detailed listing displays, from left to right, the following information about each le or directory contained within the current working directory Permissions Number of links Owner Group File count/size Last modi cation date Name

it "should respond to admin" do @usershould respond_to(:admin) end it "should not be an admin by default" do @usershould_not be_admin end

2

Here we ve used the toggle! method to flip the admin attribute from true to false Also note that the line

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