Semantic disambiguation using a statistical analysis
First Claim
Patent Images
1. A method comprising:
- receiving, by a computing device, an input natural language text including an input word;
searching a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class;
responsive to successfully identifying the matching word, identifying a first plurality of concepts associated with the matching word by the semantic register;
ranking a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class;
selecting a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class;
iterating through a second plurality of concepts associated, by the semantic register, with the pre-defined number of semantic classes, to identify a concept corresponding to the input word; and
responsive to successfully identifying the concept, associating the identified concept with the input word.
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Abstract
A text containing a word is received by a computing device. The word is compared to inventory words in a sense inventory. The sense inventory comprises at least one inventory word and at least one concept corresponding to the at least one inventory word. Upon matching the word to an inventory word in the sense inventory, a concept for the word is identified by comparing each concept related to the inventory word to the word. The concept is assigned the word.
219 Citations
20 Claims
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1. A method comprising:
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receiving, by a computing device, an input natural language text including an input word; searching a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class; responsive to successfully identifying the matching word, identifying a first plurality of concepts associated with the matching word by the semantic register; ranking a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class; selecting a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class; iterating through a second plurality of concepts associated, by the semantic register, with the pre-defined number of semantic classes, to identify a concept corresponding to the input word; and responsive to successfully identifying the concept, associating the identified concept with the input word. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system comprising:
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a storage device; and a processor operatively coupled to the storage device, the processor to; receive an input natural language text including an input word; search a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class; responsive to successfully identifying the matching word, identify a first plurality of concepts associated with the matching word by the semantic register; rank a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class; select a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class; iterate through a second plurality of concepts associated, by the semantic register, with the pre-defined number of semantic classes, to identify a concept corresponding to the input word; and responsive to successfully identifying the concept, associate the identified concept with the input word. - View Dependent Claims (10, 11, 12, 13, 14)
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15. A computer-readable non-transitory storage medium comprising executable instructions to cause a processor to:
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receive an input natural language text including an input word; search a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class; responsive to successfully identifying the matching word, identify a first plurality of concepts associated with the matching word by the semantic register; ranking a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class; selecting a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class; iterating through a second plurality of concepts associated, by the semantic register, with the identified plurality identified plurality of semantic classes, to identify a concept corresponding to the input word; and responsive to successfully identifying the concept, associate the identified concept with the input word. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification