Producing explainable rules via deep learning
AssigneeInternational Business Machines Corporation
InventorsPrithviraj Sen, Siddhartha Brahma, Yunyao Li, Laura Chiticariu, Rajasekar Krishnamurthy, Shivakumar Vaithyanathan, Marina Danilevsky Hailpern
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Abstract
A computer-implemented method according to one embodiment includes receiving, at a deep neural network (DNN), a plurality of sentences each having an associated label; training the DNN, utilizing the plurality of sentences and associated labels; and producing a linguistic expression (LE) utilizing the trained DNN.
Claims25
A computer-implemented method, comprising:
- receiving, at a deep neural network (DNN), a plurality of sentences each having an associated label;
- training the DNN, utilizing the plurality of sentences and associated labels;
- and
- producing a linguistic expression (LE) utilizing the trained DNN.
A computer program product for producing explainable rules via deep learning, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising:
- receiving, utilizing the processor at a deep neural network (DNN), a plurality of sentences each having an associated label;
- training the DNN, utilizing the processor and the plurality of sentences and associated labels;
- and
- producing a linguistic expression (LE) utilizing the trained DNN and the processor.
A system, comprising:
- a processor;
- and
- logic integrated with the processor, executable by the processor, or integrated with and executable by the processor, the logic being configured to:
- receive, at a deep neural network (DNN), a plurality of sentences each having an associated label;
- train the DNN, utilizing the plurality of sentences and associated labels;
- and
- produce a linguistic expression (LE) utilizing the trained DNN.
A computer-implemented method, comprising:
- identifying a collection of sentences having labels;
- inputting the sentences into a deep neural network (DNN) having several layers, the DNN analyzing the sentences and producing linguistic expressions (LEs) corresponding to the sentences;
- and
- in view of input from a human expert, modifying the linguistic expressions, wherein the modified linguistic expressions form a predictive model that, given an unlabeled sentence, predicts one or more labels for the unlabeled sentence.
Dependencies are inferred from the claim text.