PATENT CLAIM ANALYSIS

Application Number: 16214875
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-06
Patent Classification: ["725", "019000"]

Abstract:
A system, method and computer program utilize a distance associative hashing algorithmic means to provide a highly efficient means to rapidly address a large database. The indexing means can be readily subdivided into a plurality of independently-addressable segments where each such segment can address a portion of related data of the database where the subdivided indexes of said portions reside entirely in the main memory of each of a multiplicity of server means. The resulting cluster of server means, each hosting an addressable sector of a larger database of searchable audio or video information, provides a significant improvement in the latency and scalability of an Automatic Content Recognition system, among other uses.

Claim (Index 13):
The method of  claim 2 , wherein generating the hash value comprises:\n determining an algorithmically-derived value of the one or more pixels values, wherein the one or more pixel values are associated with a patch of the sample of the video data; subtracting a median point value established for the patch from the algorithmically-derived value; transforming a value resulting from the subtraction using a function pre-derived to distribute the value and one or more other values evenly; and generating the hash value from the transformed value.

Metadata:
- Claim Count in Document: 12.0
- Percentile: 98.0
- Lexical Diversity: 1.58667
- Patent Class: 725.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14678856', '14217039', '15240815', '15240801', '14217075']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5497678991453422
- 35 USC 102 Novelty (BERT): 0.5824204731175706
- Combined Prediction Score: 0.553033156542565
- Mean Citation Score: 400.772926
- Max Citation Score: 508.31738
- Similarity Product: 419.7680690550317

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