PATENT CLAIM ANALYSIS

Application Number: 16003540
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-12
Patent Classification: ["704", "009000"]

Abstract:
A computer-implemented method, computer system, and computer program product for improving a natural language generation knowledge base is provided. The method may include detecting user input comprising a natural language expression, generating an erroneous natural language response based on the user input and the knowledge base, determining user feedback corresponding to the erroneous natural language response, wherein the user feedback comprises an indication of an end-user reaction to the erroneous natural language response, determining an improvable performance metric with respect to the knowledge base, and updating the knowledge base based on the improvable performance metric, wherein the knowledge base comprises an explicit model of language corresponding to the erroneous natural language response, and wherein updating the knowledge base comprises updating the explicit model of language based on the user input, the erroneous natural language response, and the user feedback.

Claim (Index 5):
The computer-implemented method of  claim 4 , wherein the end-user attention monitoring comprises eye-tracking of the end-user with respect to a display instance of NLG-generated texts of the erroneous natural language response.

Metadata:
- Claim Count in Document: 21.0
- Percentile: 94.0
- Lexical Diversity: 2.86792
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14082862', '15349057', '15257266', '14617305', '15713783']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2738833467000569
- 35 USC 102 Novelty (BERT): 0.4996391635845084
- Combined Prediction Score: 0.2964589283885021
- Mean Citation Score: 173.21789600000002
- Max Citation Score: 192.86296
- Similarity Product: 116.05876095630644

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test