PATENT CLAIM ANALYSIS

Application Number: 16145378
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["704", "009000"]

Abstract:
Mechanisms, in a natural language processing (NLP) system are provided. The NLP system receives a plurality of communications associated with a communication system, over a predetermined time period, from a plurality of end user devices. The NLP system identifies, for each communication in the plurality of communications, a user submitting the communication to thereby generate a set of users comprising a plurality of users associated with the plurality of communications. The NLP system retrieves a user model for each user in the set of users, which specifies at least one attribute of a corresponding user. The NLP system generates an aggregate user model that aggregates the at least one attribute of each user in the set of users together to generate an aggregate representation of the attributes of the plurality of users in the set of users. The NLP system performs a cognitive operation based on the aggregate user model.

Claim (Index 18):
The computer program product of  claim 14 , wherein the computer readable program further causes the computing device to generate the aggregate user model at least by weighting each personality trait of each user in the set of users using a mean square weighted deviation.

Metadata:
- Claim Count in Document: 59.0
- Percentile: 97.0
- Lexical Diversity: 2.60317
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14566754', '14566741', '14566808', '14566858', '14839120']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3435607513646567
- 35 USC 102 Novelty (BERT): 0.5833928516681774
- Combined Prediction Score: 0.3675439613950088
- Mean Citation Score: 375.23137
- Max Citation Score: 502.15808
- Similarity Product: 438.06465349121095

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