PATENT CLAIM ANALYSIS

Application Number: 15863225
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["704", "009000"]

Abstract:
A company may desire to maintain a quality level for messages sent by customer service representatives to customers. The company may receive a message input by a customer service representative, modify the message with one or more neural networks, and transmit the modified message to a customer. To modify a message, an input vector may be created for each word of the message where the input vector is created using a word embedding of the word and a feature vector that represents the characters of the word. The input vectors for the words of the message may be sequentially processed with an encoding neural network to compute a message encoding vector that represents the message. The message encoding vector may then be processed by a decoding neural network to sequentially generate the words of a modified message. The modified message may then be transmitted to the customer.

Claim (Index 6):
The computer-implemented method of  claim 1 , wherein generating the modified message with the decoding neural network comprises, for each word of the modified message:\n computing a vocabulary distribution using a state vector of the decoding neural network; and selecting one or more words using the vocabulary distribution.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 86.0
- Lexical Diversity: 2.51613
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15678890', '15254041', '15254061', '15383603', '15254086']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2977948533913829
- 35 USC 102 Novelty (BERT): 0.4832883250551266
- Combined Prediction Score: 0.3163442005577573
- Mean Citation Score: 200.606412
- Max Citation Score: 212.38303
- Similarity Product: 161.23708995355008

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