Databases Reference
In-Depth Information
Algorithm 5 Compute a Matching
1: ComputeMatching( G(V , E), S i ,S e ):
2: E E \ S e
3: for each (u, v)
S i do
4: for each e adjacent on u or v in G do
5: E E \{ e }
6: end for
7: end for
8: σ A best (G (V , E ))
9: σ σ S i
10: return σ
matching among the matchings that exclude e 22 yet include e 11 . After expanding all the root's
children to the desired level, we choose the leaf with maximum weight. In this case, it is w 3 with
weight 0 . 3674. σ(w 3 ) ={ e 11 ,e 22 ,e 33 ,e 44 }
is the second-best matching (the same result as obtained
by algorithms 2 and 3 ). In the next iteration, we expand w 3 . Consider, for example, w 31 . S e (w 31 )
=
. These two edges are excluded from σ(w 31 ) . e 34 stems from σ 1 while e 33 stems from σ 2 .
The third iteration starts after all of w 3 's children are found. The node with the maximum weight
among all the nodes in the tree's frontier is now w 4 . Therefore, σ(w 4 ) ={ e 11 ,e 22 ,e 34
{ e 34 ,e 33 }
}
is chosen
to be σ 3 , the third-best matching.
Next, we prove the correctness of the algorithm.
Lemma 5.6 Procedure ComputeMatching(G(V , E), S i ,S e ) constructs a maximum weight matching
over matchings in G that contain edges from S i and do not contain edges from S e .
Proof. The correctness of the lemma follows immediately by observing that any matching in G
that contains S i and does not contain any edge from S e is also a matching in the graph G (V , E ) ,
constructed by the procedure ComputeMatching( G(V , E), S i ,S e ).
Lemma 5.7 Let w be a node in the tree T constructed by Algorithm 4 and let w 1 , ..., w t be all the
children of w in T . Then any matching satisfying constraints implied by S i (w), S e (w), and different from
σ(w)must satisfy constraints implied by S i (w j ), S e (w j ) for some j , 1
j t .
Proof. The correctness of the lemma follows by the definition of S i (w j ) , S e (w j ) , 1
j k and by
the fact that for any matching σ different from σ(w) there exists an edge e σ(w) such that e σ .
 
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