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In the last section, we used the bookmark example from Code Listing 6.2 and Figure 6.5 to give examples of how some of the elements and attributes for XUL templates could be used. Because the bookmark RDF file is quite simple, this will be a good starting point to discuss singular rules. A XUL template can have multiple rules, but the easiest case to understand is a XUL file with one rule. Code Listing 6.7 shows a XUL file that we have built to create a bookmark menu based on the RDF datasource listed in Code Listing 6.2. In Code Listing 6.7, you can see that we are associating the XUL menubar element with one datasource, bookmarks.rdf and that we are mapping the menubar element to the resource specified in the RDF file with urn:root . Of course, there is only one resource in the RDF file, but you can see that that resource is tagged with the <rdf:Description about="urn:root"> element. We know that the menubar element is tied to that resource. As we have discussed, the <template> element is the direct descendant of the <menubar> element because the menubar is now tied to that datasource. In the <conditions> section, pattern-matching rules create new variable bindings. For each match to those rules, an <action> is performed to create a menuitem. Let s go through those pattern-matching rules in detail: <content uri=" uri"> creates a new variable binding and binds the uri variable to the URI of the resource to which menubar is tied. Of course, the URI is urn:root, so this begins a set of one match:
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Linguistic variables and fuzzy sets are used as the antecedents and consequences of fuzzy rules. These rules are also called fuzzy IF THEN rules. The de nition of a fuzzy rule is given in De nition A.2. De nition A.2. A fuzzy IF THEN rule relates m antecedent variables, A1 ; A2 ; . . . ; Am , to n consequent variables, B1 ; B2 ; . . . ; Bn , and has the form IF X1 A1 AND X2 A2 ; . . . ; AND Xm Am THEN Y1 B1 AND Y2 B2 ; . . . ; AND Yn Bn where X X1 ; X2 ; . . . ; Xm and Y Y1 ; Y2 ; . . . ; Yn are linguistic variables, and A1 ; A2 ; . . . ; Am and B1 ; B2 ; . . . ; Bn are their corresponding linguistic values. Here all linguistic values are in the form of fuzzy sets with membership functions such as mAi and mBi . An example of a fuzzy IF THEN rule is IF pressure low AND temperature high THEN volume big A collection of fuzzy rules constitutes a fuzzy rule base that can be used to provide advice or decision support to input queries. A.5.2 Fuzzy Rules for Classi cation
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Obviously, support(D) is also a database over U. Comparing this definition to Definition 5.4.1, we see that U (t) =
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Slice 1 2 3 4 5 6 7 8 9 10 Total Utility 20 36 50 58 64 68 70 70 68 64 Marginal Utility 20 16 14 8 6 4 2 0 2 4
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