PATENT CLAIM ANALYSIS

Application Number: 15865716
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["725", "032000"]

Abstract:
A hardware media items scheduling and packaging system, which schedules and distributes channels to be viewed on a plurality of consumer devices, extracts contextual data from program-specific information associated with programming media content of a channel received from a distribution source device. A plurality of potential non-programming media items is determined for a plurality of users based on a match between a sentiment type of each of a plurality of non-programming media items and the extracted contextual data. Based on at least the extracted contextual data and the sentiment type of each of the plurality of potential non-programming media items, a plurality of candidate spots in the programming media content is determined. Based on at least a set of constraints and user estimation data associated with the plurality of users, a schedule of non-programming media item(s) is dynamically generated for at least one candidate spot in the programming media content.

Claim (Index 11):
The system according to  claim 1 , wherein the program-specific information corresponds to closed captions associated with live feed of the programming media content of the channel.

Metadata:
- Claim Count in Document: 56.0
- Percentile: 86.0
- Lexical Diversity: 2.26761
- Patent Class: 725.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15396453', '15396462', '15396608', '15362606', '14795863']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4501981005097402
- 35 USC 102 Novelty (BERT): 0.4872954304316967
- Combined Prediction Score: 0.4539078335019358
- Mean Citation Score: 182.015194
- Max Citation Score: 203.59302
- Similarity Product: 152.28491448263884

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