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 15):
A computer program product for determining a number of distinct logical data units in a dataset, the computer program product comprising:\n a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to randomly select, from a dataset partitioned into a set of logical data units, a number of logical data units determined by a specified sampling ratio, to serve as a sample subset of the set of logical data units; computer readable program code configured to specify a range of hash values; computer readable program code configured to calculate respective unit hash values for each of the logical data units in the sample subset; computer readable program code configured to compute a first histogram indicating a duplication count in the sample subset, of logical data units whose respective calculated unit hash values are in the specified range; computer readable program code configured to derive, from the first histogram, a second histogram indicating respective frequencies of the duplication counts in the first histogram; computer readable program code configured to derive, a third histogram of predicted duplication counts for the logical data units in the dataset whose calculated unit hash values are within the specified range of hash values, by performing an optimization method, with a target function that minimizes a distance between the second histogram and the result of applying a sampling transformation with the specified sampling ratio on candidate third histograms; and computer readable program code configured to determine, based on the third histogram, a number of distinct logical data units in the dataset.

Metadata:
- Claim Count in Document: 25.0
- Percentile: 97.0
- Lexical Diversity: 2.2381
- Patent Class: 707.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14994163', '14994161', '14994160', '15954702', '15954739']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1872572408484103
- 35 USC 102 Novelty (BERT): 0.5387491690768883
- Combined Prediction Score: 0.2224064336712581
- Mean Citation Score: 268.574112
- Max Citation Score: 379.4361
- Similarity Product: 335.1082573180676

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