PATENT CLAIM ANALYSIS

Application Number: 15997482
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["382", "159000"]

Abstract:
In one embodiment, a method includes identifying a shared visual concept in visual-media items based on shared visual features in images of the visual-media items; extracting, for each of the visual-media items, n-grams from communications associated with the visual-media item; generating, in a d-dimensional space, an embedding for each of the visual-media items at a location based on the visual concepts included in the visual-media item; generating, in the d-dimensional space, an embedding for each of the extracted n-grams at a location based on a frequency of occurrence of the n-gram in the communications associated with the visual-media items; and associating, with the shared visual concept, the extracted n-grams that have embeddings within a threshold area of the embeddings for the identified visual-media items.

Claim (Index 18):
The media of  claim 17 , wherein the location of the embedding for each of one or more extracted n-grams is based on a triplet-loss algorithm, wherein the triplet-loss algorithm analyzes a plurality of information triplets, each of the information triplets comprising:\n a media-item identifier corresponding to a particular visual-media item including a particular visual concept; a positive n-gram, wherein the positive n-gram is an n-gram that is included in a number of communications associated with the particular visual-media item that is greater than a threshold number; and a negative n-gram, wherein the negative n-gram is an n-gram that is not included in a minimum number of communications associated with the particular visual-media item.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 94.0
- Lexical Diversity: 2.60377
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15277950', '15365789', '14952707', '15728189', '15286315']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3127545106756398
- 35 USC 102 Novelty (BERT): 0.5334060482825943
- Combined Prediction Score: 0.3348196644363352
- Mean Citation Score: 260.511536
- Max Citation Score: 356.84348
- Similarity Product: 299.72216089514257

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

Dataset: test