SUPERVISED MACHINE LEARNING METHOD FOR MATCHING UNSUPERVISED DATA
A method including receiving first and second natural language texts. A distance metric is generated from the first and second natural language texts. A first machine learning system is executed, the first machine learning system taking, as a first input, the distance metric and generating, as a fir...
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| creator | BAR ELIYAHU, NATALIE BECHLER, SIGALIT LACKRITZ, HADAR TAYEB, YAAKOV |
| description | A method including receiving first and second natural language texts. A distance metric is generated from the first and second natural language texts. A first machine learning system is executed, the first machine learning system taking, as a first input, the distance metric and generating, as a first output, a first probability that the first natural language text matches the second natural language text. A second machine learning system is executed, the second machine learning system taking as a second input the first natural language text and as a third input the second natural language text, and generating, as a second output, a second probability that the first natural language text matches the second natural language text. A third probability that the first natural language text matches the second natural language text is generated. Generating includes combining the first probability and the second probability. |
| format | Patent |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | SUPERVISED MACHINE LEARNING METHOD FOR MATCHING UNSUPERVISED DATA |
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