PATENT CLAIM ANALYSIS

Application Number: 16141615
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["705", "038000"]

Abstract:
Systems and methods are described herein for learning an entity's trust model and risk tolerance. An entity's trust score may be calculated based on data from a variety of data sources, and this data may be combined according to a set of weights which reflect an entity's trust model and risk tolerance. For example, an entity may weight data of a certain type more heavily for certain types of transactions and another type of data more heavily for other transactions. By gathering data about the entity, a system may predict the entity's trust model and risk tolerance and adjust the set of weights accordingly for calculating trust scores. Furthermore, by monitoring how entities adjust weights for different transaction types, default weighting profiles may be created that are customized for specific transaction types. As another example, an entity's trust score, as reported to a requesting entity, may be adjusted based on that requesting entity's own trust model, or how “trusting” the requesting entity is.

Claim (Index 11):
A system for adjusting, for a requesting entity, a trust score for a second entity, the system comprising:\n processing circuitry configured to:\n determine a baseline trust score for the second entity; \n receive data about the requesting entity from a first remote source; \n calculate a trusting adjustment score for the requesting entity based on the received data from the first remote source; \n determine an adjusted trust score for the second entity by combining the trusting adjustment score and the baseline trust score for the second entity; and \n transmit to the requesting entity an indication of the adjusted trust score.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 97.0
- Lexical Diversity: 2.21429
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15079952', '15630299', '15055952', '15056484', '15406405']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1392688888254973
- 35 USC 102 Novelty (BERT): 0.6049171026308673
- Combined Prediction Score: 0.1858337102060343
- Mean Citation Score: 374.761302
- Max Citation Score: 481.74612
- Similarity Product: 376.3482198099733

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

Dataset: test