PATENT CLAIM ANALYSIS

Application Number: 16235290
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-07
Patent Classification: ["707", "722000"]

Abstract:
Computer vision for unsuccessful queries and iterative search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and describing them, e.g., using feature vectors. In some aspects, these visual characteristics are determined for search queries that are identified as not being successful. Aggregated information describing visual characteristics of images of unsuccessful search queries is used to determine common visual characteristics and objects depicted in those images. This information can be used to inform other users about unmet needs of searching users. In some aspects, these visual characteristics are used in connection with iterative image searches where users select an initial query image and then the search results are iteratively refined. Unlike conventional techniques, the described system iteratively refines the returned search results using an embedding space learned from binary attribute labels describing images.

Claim (Index 18):
A system comprising:\n a machine learning module implemented at least partially in hardware of at least one computing device to recognize objects and visual characteristics of the objects in digital images using one or more machine learning models; a search module implemented at least partially in the hardware of the at least one computing device to receive search queries including digital images and generate search results having similar digital images to the digital images of the search queries based on recognized objects and recognized visual characteristics recognized by the one or more machine learning models; an unsuccessful query module implemented at least partially in the hardware of the at least one computing device to identify the search queries that are not successful in locating a suitable digital image based on user feedback in relation to a corresponding search result; and a search aggregation module implemented at least partially in the hardware of the at least one computing device to aggregate data that is derived from the identified search queries that are not successful based on common-object recognition by the one or more machine learning models.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 1.81176
- Patent Class: 707.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15616776', '15619205', '13297521', '12507276', '15277950']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1905346985062994
- 35 USC 102 Novelty (BERT): 0.4755323594076867
- Combined Prediction Score: 0.2190344645964382
- Mean Citation Score: 168.871568
- Max Citation Score: 184.72725
- Similarity Product: 139.26721550054847

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

Dataset: test