In this paper, we present a tree-based model to perform fast linear time q-gram matching. All q-grams present in the text are stored in a tree structure similar ...
In this paper, we present a tree-based model to perform fast linear time q{\hbox{-}}{\rm gram} matching. All q{\hbox{-}}{\rm grams} present in the text are ...
In this paper, we present a tree-based model to perform fast linear time q{\hbox{-}}{\rm gram} matching. All q{\hbox{-}}{\rm grams} present in the text are ...
This paper presents a tree-based model to perform fast linear time q-gram matching, using a tree redundancy pruning algorithm to reduce the size of the tree ...
In this paper, we present a tree-based model to perform fast linear time q-gram matching. All q-grams present in the text are stored in a tree structure similar ...
In this paper, we present a tree-based model to perform fast linear time q-gram matching. All q-grams present in the text are stored in a tree structure similar ...
In this paper, we present a tree-based model to perform fast linear time q{\hbox{-}}{\rm gram} matching. All q{\hbox{-}}{\rm grams} present in the text are ...
q-gram approximate matching optimisations - Stack Overflow
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Dec 21, 2009 · tree ... I have a table containing 3 million people records on which I want to perform fuzzy matching using q-grams (on surname for instance).
Both algorithms first compute a match between the nodes of the trees, and based on the match the distance is computed in O(ne) time, where e is the edit ...
Aided by a preprocessed query sequence, the blast algorithm efficiently locates and extends each seed to a local alignment containing the seed. However, it is ...