PATENT CLAIM ANALYSIS

Application Number: 15916422
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["709", "206000"]

Abstract:
In one embodiment, a processor receives data indicative of a plurality of conversations involving a primary user. The processor identifies a subset of the plurality of conversations that are regarding a particular topic. The processor adds a conversation to the subset based on a match between one or more keywords in the conversation matching a list of keywords associated with the particular topic. The processor uses a machine learning-based model to identify one or more context characteristics of the conversations in the identified subset. The processor updates the subset of conversations by adding at least one of the conversations to the subset based on the at least one conversation having at least one context characteristic identified by the machine learning-based model. The processor provides data indicative of the updated subset of conversations to a user interface for review by the primary user.

Claim (Index 8):
The method as in  claim 1 , further comprising:\n capturing the data indicative of the plurality of conversations involving the primary user by comparing one or more locations of the primary user to a set of locations at which audio capture is authorized.

Metadata:
- Claim Count in Document: 42.0
- Percentile: 90.0
- Lexical Diversity: 2.48333
- Patent Class: 709.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15717787', '15793691', '15660399', '14094730', '15854642']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2065105242461108
- 35 USC 102 Novelty (BERT): 0.4763410752681299
- Combined Prediction Score: 0.2334935793483127
- Mean Citation Score: 145.5894
- Max Citation Score: 151.55937
- Similarity Product: 106.9245312927264

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

Dataset: test