PATENT CLAIM ANALYSIS

Application Number: 15873002
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-07
Patent Classification: ["708", "607000"]

Abstract:
A method for multiplying a first sparse matrix by a second sparse matrix in an associative memory device includes storing multiplicand information related to each non-zero element of the second sparse matrix in a computation column of the associative memory device; the multiplicand information includes at least a multiplicand value. According to a first linear algebra rule, the method associates multiplier information related to a non-zero element of the first sparse matrix with each of its associated multiplicands, the multiplier information includes at least a multiplier value. The method concurrently stores the multiplier information in the computation columns of each associated multiplicand. The method, concurrently on all computation columns, multiplies a multiplier value by its associated multiplicand value to provide a product in the computation column, and adds together products from computation columns, associated according to a second linear algebra rule, to provide a resultant matrix.

Claim (Index 14):
The method of  claim 13  wherein said storing a vector value also comprises:\n concurrently searching all computation columns having matrix row index identical to each vector index and concurrently storing a vector value from said vector index in all computation columns found by said searching.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 86.0
- Lexical Diversity: 2.63333
- Patent Class: 708.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14580110', '14314750', '11673944', '14400834', '13009100']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4298890407073817
- 35 USC 102 Novelty (BERT): 0.5190436363595039
- Combined Prediction Score: 0.438804500272594
- Mean Citation Score: 249.427276
- Max Citation Score: 266.53076
- Similarity Product: 186.435858358047

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test