PATENT CLAIM ANALYSIS

Application Number: 16278524
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-08
Patent Classification: ["708", "250000"]

Abstract:
An improved pseudo-random number generator is introduced that has increased security due to higher randomness and lower predictability. The PRNG uses seed values that are based on a combination of various selectable values from the real-world that are typically made publicly available over a computer network (i.e., the Internet), such as: one or more weather conditions at a particular time or date and geographic location, a score of a sports event, a stock market index or ticker value, an election vote total, attendance at a cultural event, gross dollar sales from a movie release, and other such numerically quantifiable values that, individually and in combination, are impossible to exactly predict in advance, yet are precisely verifiable after the number-generating event using electronically-stored information. The improved pseudo-random number generator may be used for more secure determination of lottery outcomes and the like.

Claim (Index 7):
The apparatus of  claim 1 , wherein the software application comprises a lottery contest, the output is a pseudo-random sequence of data generated from the at least one seed value in each of the at least two seed categories, and a winner of the lottery contest is determined by said matching of the user pseudo-random sequence with the pseudo-random data sequence.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 99.0
- Lexical Diversity: 1.49057
- Patent Class: 708.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15671758', '13466974', '12826077', '13595446', '13229668']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3837976290370499
- 35 USC 102 Novelty (BERT): 0.5137965613245784
- Combined Prediction Score: 0.3967975222658028
- Mean Citation Score: 166.12098400000005
- Max Citation Score: 293.37534
- Similarity Product: 273.1849169466054

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