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Dynamic match search

Match-Search with Caps the Dynamic Match-search Algorithm... [Pg.89]

Therefore, a further improvement of the match-search algorithm was developed the dynamic match-search algorithm. The new algorithm extends the dy-... [Pg.89]

In order to build an MTree model from more than two Feature Trees, the dynamic match-search algorithm can be applied in a hierarchical manner. We developed two efficient heuristics for this task ... [Pg.91]

Fig. 4.7 (a) Three of the 10 actives (colored red) used to select the final subset are shown with two unknowns (colored black) found amongst their nearest neighbors. The Feature Tree similarity values (calculated with the dynamic match-search algorithm)... [Pg.96]

Fig. 4.4 The match search algorithm creates a matrix with one cell for each pair ofdirected tree edges. The cell stores the overall similarity of the two subtrees. The similarity value is calculated with a dynamic programming scheme shown on the right. First, an extension match (blue ellipsoid) is searched. Then the subtrees are cut and matched in all possible combinations. For each combination, a similarity value can be extracted from the matrix (exemplarily shown by the blue arrows). A maximum-weight bipartite matching solves the assignment of the subtrees. Fig. 4.4 The match search algorithm creates a matrix with one cell for each pair ofdirected tree edges. The cell stores the overall similarity of the two subtrees. The similarity value is calculated with a dynamic programming scheme shown on the right. First, an extension match (blue ellipsoid) is searched. Then the subtrees are cut and matched in all possible combinations. For each combination, a similarity value can be extracted from the matrix (exemplarily shown by the blue arrows). A maximum-weight bipartite matching solves the assignment of the subtrees.
Fig. 4.12 A chemistry space can be searched for the compound most similar to a query with the following dynamic programming procedure. For every directed edge and every link type, a list of the most similar fragments is calculated with the match-search algorithm. When a second link is found in the fragment, the dynamic programming matrix can be used in order to find the highest possible similarity value (red arrow, the part of the query which has to be matched to the link blue arrows, the compatible link types green arrows, previously calculated similarity values for these edge-link-type combinations). Fig. 4.12 A chemistry space can be searched for the compound most similar to a query with the following dynamic programming procedure. For every directed edge and every link type, a list of the most similar fragments is calculated with the match-search algorithm. When a second link is found in the fragment, the dynamic programming matrix can be used in order to find the highest possible similarity value (red arrow, the part of the query which has to be matched to the link blue arrows, the compatible link types green arrows, previously calculated similarity values for these edge-link-type combinations).
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