PATENT CLAIM ANALYSIS

Application Number: 16437715
Application Type: Utility
Filing Date: 2019-06
Publication Date: 2019-09
Patent Classification: ["715", "760000"]

Abstract:
In embodiments of document layer extraction for mobile devices, an image service can receive a request from a mobile device for a multi-layered image, and the image service generates a layer extraction as a full-resolution image of each of the layers of the multi-layered image. The image service can then generate a component representation of the layer extractions that correspond to selected layers of the multi-layered image, where the layer extractions are independently editable in the component representation. The image service can then communicate the component representation of the layer extractions that are independently editable and correspond to the selected layers of the multi-layered image to the mobile device for use with an image editing application on the mobile device, and the image service receives image edit changes made to one or more of the selected layers in the component representation of the multi-layered image from the mobile device.

Claim (Index 20):
The computing device as recited in  claim 17 , wherein the imaging application is implemented to receive image edit changes made to one or more of the selected layers in the component representation of the multi-layered image from the mobile device.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 100.0
- Lexical Diversity: 2.78571
- Patent Class: 715.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14668742', '15417272', '13436656', '14667790', '13233882']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.34713572860251
- 35 USC 102 Novelty (BERT): 0.6125037819721567
- Combined Prediction Score: 0.3736725339394747
- Mean Citation Score: 267.75438599999995
- Max Citation Score: 605.52203
- Similarity Product: 486.1055783902544

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