PATENT CLAIM ANALYSIS

Application Number: 16383405
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2019-08
Patent Classification: ["717", "124000"]

Abstract:
Duplicate bug report detection using machine learning algorithms and automated feedback incorporation is disclosed. For each set of bug reports, a user-classification of the set of bug reports as including duplicate bug reports or non-duplicate bug reports is identified. Also for each set of bug reports, correlation values corresponding to a respective feature, of a plurality of features, between bug reports in the set of bug reports is identified. Based on the user-classifications and the correlation values, a model is generated to identify any set of bug reports as including duplicate bug reports or non-duplicate bug reports. The model is applied to classify a particular bug report and a candidate bug report as duplicate bug reports or non-duplicate bug reports.

Claim (Index 2):
The one or more media of  claim 1 , further storing instructions which, when executed by the one or more processors, cause:\n determining a third correlation value, corresponding to a second feature, between the particular bug report and the first bug report; determining a fourth correlation value, corresponding to the second feature, between the particular bug report and the second bug report; based on at least the third correlation value and the fourth correlation value, determining a second aggregated correlation value, corresponding to the second feature, between the particular bug report and the first bug report; applying the classification model to at least the first aggregated correlation value and the second aggregated correlation value to obtain the classification of the particular bug report and the first bug report.

Metadata:
- Claim Count in Document: 13.0
- Percentile: 100.0
- Lexical Diversity: 2.40741
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14992831', '15065214', '15655187', '13931779', '13242936']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3718930912190243
- 35 USC 102 Novelty (BERT): 0.5473809792367852
- Combined Prediction Score: 0.3894418800208004
- Mean Citation Score: 225.756748
- Max Citation Score: 361.46432
- Similarity Product: 249.8899921234131

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

Dataset: test