PATENT CLAIM ANALYSIS

Application Number: 16112611
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2018-12
Patent Classification: ["709", "206000"]

Abstract:
Examples are generally directed towards context-sensitive generation of conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of training context-message-response n-tuples. A response generation engine is trained on the set of training context-message-response n-tuples. The trained response generation engine automatically generates a context-sensitive response based on a user generated input message and conversational context data. A digital assistant utilizes the trained response generation engine to generate context-sensitive, natural language responses that are pertinent to user queries.

Claim (Index 3):
The system of  claim 2 , wherein the at least one processor further executes the extraction component to:\n extract the context-message-response n-tuples from at least one social media source, wherein the at least one social media source provides the conversational context data in at least one format, wherein a format of the conversational data comprises at least one of a text format, an audio format, or a visual format.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 96.0
- Lexical Diversity: 1.75
- Patent Class: 709.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14726562', '14726569', '15816282', '11580926', '15672424']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.283907004497646
- 35 USC 102 Novelty (BERT): 0.5656477483857072
- Combined Prediction Score: 0.3120810788864521
- Mean Citation Score: 264.69212400000004
- Max Citation Score: 439.5038
- Similarity Product: 401.67520970652106

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