Graph-based ranking algorithms for text processing
First Claim
1. A method of processing at least one natural language text using a graph, comprising:
- selecting, using a processing unit, a plurality of text units from said at least one natural language text;
associating, using the processing, unit, the plurality of text units with a plurality of graph nodes such that each graph node corresponds to one of the text units selected from said at least one natural language text;
determining, using the processing unit, at least one connecting relation between at least two of the plurality of text units;
associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes;
constructing, using the processing unit, a graph using only the plurality of graph nodes that correspond to one of the text units selected from said at least one natural language text and said at least one graph edge; and
determining, using the processing unit, at least one ranking by applying a graph-based ranking algorithm to the graph, wherein determining the at least one ranking comprises ranking the plurality of graph nodes based upon the at least one graph edge so that the ranking represents the relative importance, within the natural language text, of the text units associated with the graph nodes, and wherein ranking the plurality of graph nodes based upon the at least one graph edge comprises;
assigning a plurality of first scores to the plurality of graph nodes;
defining a relationship between a second score of each graph node and second scores, of graph nodes coupled to each graph node by a graph edge; and
determining a plurality of second scores associated with the plurality of graph nodes by applying an iterative recursive algorithm starting with the first plurality of scores and iterating until the relationship is satisfied.
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Abstract
The present invention provides a method of processing at least one natural language text using a graph. The method includes determining a plurality of text units based upon the natural language text, associating the plurality of text units with a plurality of graph nodes, and determining at least one connecting relation between at least two of the plurality of text units. The method also includes associating the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes and determining a plurality of rankings associated with the plurality of graph nodes based upon the at least one graph edge. The method can also include a graphical visualization of at least one important text unit in a natural language text or collection of texts. Methods for word sense disambiguation, keyword extraction, and sentence extraction are also provided.
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Citations
47 Claims
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1. A method of processing at least one natural language text using a graph, comprising:
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selecting, using a processing unit, a plurality of text units from said at least one natural language text; associating, using the processing, unit, the plurality of text units with a plurality of graph nodes such that each graph node corresponds to one of the text units selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of text units; associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that correspond to one of the text units selected from said at least one natural language text and said at least one graph edge; and determining, using the processing unit, at least one ranking by applying a graph-based ranking algorithm to the graph, wherein determining the at least one ranking comprises ranking the plurality of graph nodes based upon the at least one graph edge so that the ranking represents the relative importance, within the natural language text, of the text units associated with the graph nodes, and wherein ranking the plurality of graph nodes based upon the at least one graph edge comprises; assigning a plurality of first scores to the plurality of graph nodes; defining a relationship between a second score of each graph node and second scores, of graph nodes coupled to each graph node by a graph edge; and determining a plurality of second scores associated with the plurality of graph nodes by applying an iterative recursive algorithm starting with the first plurality of scores and iterating until the relationship is satisfied. - View Dependent Claims (2, 4, 5, 6, 7, 8)
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3. A method of processing at least one natural language text using a graph, comprising:
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selecting, using a processing unit, a plurality of text units from said at least one natural language text; associating, using the processing unit, the plurality of text units with a plurality of graph nodes such that each graph node corresponds to one of the text units selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of text units; associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that correspond to one of the text units selected from said at least one natural language text and said at least one graph edge; and determining, using the processing unit, at least one ranking by applying a graph-based ranking algorithm to the graph, wherein said at least one graph edge comprises a plurality of graph edges and wherein determining said at least one ranking comprises ranking the graph edges based upon the plurality of graph nodes and wherein ranking the graph edges based upon the plurality of graph nodes comprises; assigning a first score to each graph edge; defining a relationship between a second score of each graph edge and second scores of graph edges coupled to a common graph node; and determining a second score associated with each graph edge by applying an iterative recursive algorithm and iterating until the relationship is satisfied. - View Dependent Claims (9)
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10. A method of disambiguating word senses in at least one natural language text using a graph, comprising:
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selecting, using a processing unit, a plurality of text units from said at least one natural language text; associating, using the processing unit, at least one word sense with each text unit selected from said at least one natural language text; associating, using the processing unit, the plurality of word senses with a plurality of graph nodes such that each graph node corresponds to one of the word senses that is associated with a text unit selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of word senses; associating, using the processing unit, said at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that are associated with one of the text units selected from said at least one natural language text and said at least one graph edge ranking, using the processing unit, the plurality of graph nodes by applying a graph-based ranking algorithm to the graph so that the ranking represents the relative importance, within said at least one natural language text, of the word senses associated with the text units; and selecting, using the processing unit, one word sense for each text unit based on the plurality of rankings. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A method of keyword extraction from at least one natural language text using a graph, comprising:
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selecting, using a processing unit, a plurality of text units from said at least one natural language text; associating, using the processing unit, the plurality of text units with a plurality of graph nodes so that each graph node is associated with one of the plurality of text units selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of text units; associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that are associated with one of the text units selected from said at least one natural language text and said at least one graph edge; ranking, using the processing unit, the plurality of graph nodes by applying a graph-based ranking algorithm to the graph; and determine, using the processing unit, at least one keyword based on the plurality of text units and the plurality of rankings. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31)
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32. A method of sentence extraction from at least one natural language text using a graph, comprising:
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selecting, using the processing unit, a plurality of sentences from said at least one natural language text; associating, using the processing unit, the plurality of sentences with a plurality of graph nodes so that each graph node is associated with one of the plurality of sentences selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of sentences; associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that are associated with one of the text units selected from said at least one natural language text and said at least one graph edge; ranking, using the processing unit, the plurality of graph nodes by applying a graph-based ranking algorithm to the graph; and selecting, using the processing unit, at least one of the plurality of sentences based on the plurality of text units and the plurality of rankings. - View Dependent Claims (33, 34, 35, 36, 37, 38, 39, 40, 41, 42)
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43. A method for graphical visualization of a natural language text, comprising:
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selecting, using a processing unit, a plurality of text units from the natural language text; associating, using the processing unit, the plurality of text units with a plurality of graph nodes so that each graph node is associated with one of the text units selected from the natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of text units; associating, using the processing unit, the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that are associated with one of the text units selected from the natural language text and said at least one graph edge; ranking, using the processing unit, the plurality of graph nodes by applying a graph-based algorithm to the graph; and providing, using the processing unit, a visual indication for each text unit based on the plurality of rankings. - View Dependent Claims (44, 45, 46, 47)
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Specification