PATENT CLAIM ANALYSIS

Application Number: 16417148
Application Type: Utility
Filing Date: 2019-05
Publication Date: 2019-11
Patent Classification: ["706", "021000"]

Abstract:
Systems and methods for generating a slate of ranked items are provided. In one example embodiment, a computer-implemented method includes inputting a sequence of candidate items into a machine-learned model, and obtaining, in response to inputting the sequence of candidate items into the machine-learned model, an output of the machine-learned model that includes a ranking of the candidate items that presents a diverse set of the candidate items at the top positions in the ranking such that one or more highly relevant candidate items can be demoted in the ranking.

Claim (Index 1):
A computer system comprising:\n one or more processors; and one or more non-transitory computer readable media that collectively store: a machine-learned pointer network for generating an output sequence from a list of candidate items, the machine-learned pointer network comprising:\n an encoder network configured to receive the list of candidate items and provide an output that includes a sequence of latent memory states; \n a decoder network configured to receive a previously-selected candidate item for the output sequence and provide an output vector based at least in part on the previously-selected candidate item; and \n an attention network configured to receive the sequence of latent memory states and a query including the output vector from the decoder network, the attention network configured to produce a probability distribution associated with a next candidate item to include in the output sequence, wherein the attention network produces the probability distribution based at least in part on candidate items that already appear in the output sequence; and \n instructions that, when executed by the one or more processors, cause the computer system to perform operations, the operations comprising:\n providing an input associated with the list of candidate items to the machine-learned pointer network; \n implementing the machine-learned pointer network to process the list of candidate items; \n receiving an output generated by the machine-learned pointer network as a result of processing the list of candidate items; and \n selecting the next candidate item to include in the output sequence based at least in part on the probability distribution.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 100.0
- Lexical Diversity: 1.92
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15975731', '15469981', '14586202', '15475016', '15381637']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3662901272528772
- 35 USC 102 Novelty (BERT): 0.4830121522584862
- Combined Prediction Score: 0.3779623297534381
- Mean Citation Score: 185.953252
- Max Citation Score: 205.69078
- Similarity Product: 148.3724969696319

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