PATENT CLAIM ANALYSIS

Application Number: 16121696
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["707", "692000"]

Abstract:
Methods, computing systems and computer program products implement embodiments of the present invention that include partitioning a dataset into a full set of logical data units, and selecting a sample subset of the full set, the sample subset including a random sample of the full set based on a sampling ratio. A set of target hash values are selected from a full range of hash values, and, using a hash function, a respective unit hash value is calculated for each of the logical data units in the sample subset. A histogram is computed that indicates a duplication count of each of the unit hash values that matches a given target hash value, and based on the histogram, a number of distinct logical data units in the full set is estimated.

Claim (Index 12):
The apparatus according to  claim 11 , wherein the processor is configured to determine, based on the third histogram, the number of distinct logical data units in the dataset by estimating, based on the third histogram, a number of distinct logical data units in the dataset that are in the specified range of hash values, and extrapolating, based on a ratio between the subrange and the full range of the hash values, the number of distinct logical data units in the dataset that are in the full range of hash values.

Metadata:
- Claim Count in Document: 25.0
- Percentile: 97.0
- Lexical Diversity: 2.2381
- Patent Class: 707.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14994163', '14994161', '14994160', '15954702', '15954739']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2066667104630442
- 35 USC 102 Novelty (BERT): 0.5405479298631083
- Combined Prediction Score: 0.2400548324030506
- Mean Citation Score: 268.574112
- Max Citation Score: 379.4361
- Similarity Product: 303.4496222235203

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

Dataset: test