PATENT CLAIM ANALYSIS

Application Number: 15776135
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-11
Patent Classification: ["711", "100000"]

Abstract:
Proposed are a storage apparatus and a control method thereof capable of improving the response performance to a read access of various access patterns. When data to be read is not retained in a data buffer memory, upon staging the data to be read, a processor performs sequential learning of respectively observing an access pattern in units of blocks of a predetermined size and an access pattern in units of slots configured from a plurality of the blocks regarding an access pattern of the read access from the host apparatus, and expands a data range to be staged as needed based on a learning result of the sequential learning.

Claim (Index 10):
The control method of a storage apparatus according to  claim 9 ,\n wherein, in the first step, the processor learns, for each access area configured from a plurality of the slots, an access pattern of the read access to the access area in units of the slots; and wherein, in the second step, the processor, even when continuity of an access destination of the read access in the block units or the slot units could not be detected as the access pattern of the read access, expands the data range to be staged when a count of the read access to the access area exceeds a threshold.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 93.0
- Lexical Diversity: 1.9322
- Patent Class: 711.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14904813', '13964787', '12007531', '13263996', '12889559']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5266381701277009
- 35 USC 102 Novelty (BERT): 0.47484998732751
- Combined Prediction Score: 0.5214593518476818
- Mean Citation Score: 156.149676
- Max Citation Score: 162.86086
- Similarity Product: 117.12369890050768

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