PATENT CLAIM ANALYSIS

Application Number: 15937916
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-10
Patent Classification: ["725", "086000"]

Abstract:
Systems and methods for making video content recommendations. Metadata relating to at least one content item consumed by the user is received. The video data is stored as at least one video data file for each of the content items and frame change times are extracted for each of the content items from corresponding of the at least one video data file. Frame image files are created for each of the content items based on corresponding sets of the frame times and entity data is extracted from the frame files. Audio data of each of the content items is converted to text data and the entity data and the text data are merged for each content item to create a list of tokens corresponding to each content item. A document vector is determined for each content item based on the list of tokens corresponding to that content item and the similarity of each item of content to each item in a different set of content items is determined based on the vectors. Recommendations of content are presented to a user based on the scores.

Claim (Index 10):
A method for making video content recommendations based on video content consumed by a user, the method comprising:\n receiving metadata relating to at least one content item consumed by the user, the content including video data and audio data; storing the video data as at least one video data file for each of the content items; extracting frame change times for each of the content items from corresponding of the at least one video data file; creating frame image files for each of the content items based on corresponding sets of the frame change times; extracting entity data for each content item from the sets of frame image files, wherein the entity data indicates semantic concepts related to at least one object represented in the corresponding frame image file; converting the audio data of each of the content items to text data; merging the entity data and the text data for each content item to create a list of tokens corresponding to each content item based on an id of the content item; calculating a document vector for each content item based on the list of tokens corresponding to that content item, whereby the document vector is a representation of objects represented in the content item; scoring the similarity of each item of content to each item in a different set of content items based on the vectors; present to the user content items in the different set of content items based on the scoring step.

Metadata:
- Claim Count in Document: 71.0
- Percentile: 90.0
- Lexical Diversity: 2.89394
- Patent Class: 725.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['11465967', '13458897', '14688691', '13831202', '14885924']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4258051063199441
- 35 USC 102 Novelty (BERT): 0.483612042599336
- Combined Prediction Score: 0.4315857999478834
- Mean Citation Score: 166.265226
- Max Citation Score: 179.76697
- Similarity Product: 123.84585766380908

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