PATENT CLAIM ANALYSIS

Application Number: 15991453
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-12
Patent Classification: ["708", "200000"]

Abstract:
Systems and methods are provided for bounded error matching of large scale numeric datasets. For example, a method includes generating a first synopsis for a first numeric dataset maintained in a data repository, receiving a user query to search for numeric datasets in the data repository which are related to a second numeric dataset, generating a second synopsis of the second numeric dataset, performing a hounded error matching process based on an error threshold value by comparing the second synopsis to the first synopsis to determine a match score between the first and second numeric datasets, the match score providing a measure of similarity between the first and second synopses, and responsive to results of the bounded error matching process, returning a query result to the user, which includes an identification of the first numeric dataset and the determined match score between the first and second numeric datasets.

Claim (Index 9):
The method of  claim 1 , wherein the first and second numeric datasets comprise multi-dimensional numerical elements, and wherein the method further comprises mapping the multi-dimensional numerical elements of the first and second numeric dataset to one-dimensional numerical elements prior to generating the first and second synopsis data structures.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 2.54839
- Patent Class: 708.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['12022601', '14672516', '13175611', '11906614', '14995090']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.392293825008247
- 35 USC 102 Novelty (BERT): 0.5063528664626262
- Combined Prediction Score: 0.4036997291536849
- Mean Citation Score: 174.678348
- Max Citation Score: 192.20882
- Similarity Product: 124.68386787634611

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

Dataset: test