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 3):
A method as described in  claim 1 , wherein the identifying is based on user feedback for a corresponding search result indicating that the corresponding search result is not satisfactory.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 1.81176
- Patent Class: 707.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15616776', '15619205', '13297521', '12507276', '15277950']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2041676068715428
- 35 USC 102 Novelty (BERT): 0.5097085633254235
- Combined Prediction Score: 0.2347217025169309
- Mean Citation Score: 168.871568
- Max Citation Score: 184.72725
- Similarity Product: 98.746735301435

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