Xerox Corporation

Matthias Galle

Jean-Michel Renders

Matias D Tealdi

Guillaume Jacquet

A system and method of identifying repeat subsequences having at least a value of x for threshold of different left contexts and a value of y for a threshold of different right contexts for an input sequence are disclosed. The method may include generating a lexicographically sorted suffix array for the input sequence and a longest common prefix array. The suffix array is traversed in lexicographic order comparing the longest common prefix values between consecutive suffixes. Suffixes with the same longest common prefix are representative of occurrence of the same repeat, a higher longest common prefix indicates a new occurrence of a longer repeat, and a lower longest common prefix indicates the last occurrence of a repeat.

Identifying repeat subsequences by left and right contexts

A method, system, and computer program product for extracting text motifs from the electronic documents is disclosed. A user provides a largest-maximal repeat or a super-maximal repeat as a first text block. The occurrences of the first text block are detected to identify the second text blocks in the vicinity of the occurrences of the first text block on the basis of pre-defined parameters. The text motifs are determined by combining the first text block and the second text block. Finally, the text motifs are extracted from the electronic documents.

Method and system for motif extraction in electronic documents

A method of updating a suffix tree includes providing an initial suffix tree based on a first sequence of symbols drawn from an alphabet. The suffix tree includes existing nodes representing respective subsequences occurring in the first sequence of symbols. The existing nodes are associated with information relating to membership of the subsequences in at least one class of repeat subsequences. A second sequence of symbols is received and the initial suffix tree is updated to form an updated suffix tree by adding new nodes representing subsequences occurring in the second sequence of symbols that are not represented by the existing nodes. The subsequences represented by the new nodes are ordered in a new node data structure which is processed to updating the information relating to the at least one class of repeat subsequences associated with at least some of the nodes in the updated suffix tree.

Incremental computation of repeats

A method for reconstruction includes providing a directed input graph generated from a set of n-grams and statistics for the n-grams, edges of the graph being joined through nodes of the graph. Each edge has an associated label and a multiplicity of at least one. Each of the n-grams in the set being represented by a respective one of the labels, whereby a Eulerian cycle through the graph traverses each edge the respective multiplicity of times. Reduction rules are applied iteratively to generate a refined graph which is both irreducible and equivalent to the input graph. Information is output based on the labels of the refined graph.

[object Object]

A system and method for representing a textual document based on the occurrence of repeats are disclosed. The system includes a sequence generator which defines a sequence representing words forming a collection of documents. A repeat calculator identifies a set of repeats within the sequence, the set of repeats comprising subsequences of the sequence which each occur more than once. A representation generator generates a representation for at least one document in the collection of documents based on occurrence, in the document, of repeats from the set of repeats.

Bag-of-repeats representation of documents

A method for clustering documents is provided. Each document is represented by a multidimensional data point. The data points are initially assigned to a respective cluster and serve as their initial representative points. Thereafter, in an iterative process, the data points are clustered among the clusters, by assigning the data points to the clusters based on a comparison measure of each data point with the cluster or its representative point, and a threshold of the comparison measure. Based on this clustering, a new representative point for each of the clusters can be computed. Optionally, overlapping clusters are merged. For the next iteration, the new representative points are used as the representative points. An assignment of the documents to the clusters is output, based on a clustering of the data points in the latest iteration. Multiple batches may be processed, retaining the initial clusters to which the original batch was assigned.

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St-Martin d'Heres, France

Matthias Galle