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 5):
The method of  claim 3 , further comprising:\n performing a neighborhood preservation process on the first numeric data set, thereby generating a first neighborhood preserved dataset based on the numerical elements of the first numeric dataset, the first truncated dataset, and the error threshold value; wherein generating the first synopsis data structure of the first numeric dataset comprises generating the first synopsis data structure using the first truncated dataset and the first neighborhood preserved dataset.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 2.54839
- Patent Class: 708.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['12022601', '14672516', '13175611', '11906614', '14995090']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3607170057174896
- 35 USC 102 Novelty (BERT): 0.5194781484527566
- Combined Prediction Score: 0.3765931199910163
- Mean Citation Score: 174.678348
- Max Citation Score: 192.20882
- Similarity Product: 103.436984123137

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