PATENT CLAIM ANALYSIS

Application Number: 16215491
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-06
Patent Classification: ["726", "023000"]

Abstract:
Systems and methods for utilizing statistical relational learning techniques in order to predict factors for nodes of a node graph, such as a node graph that represents attacks and incidents to a computing system, are described. In some embodiments, the systems and methods identify certain nodes (of a node graph) as representing malicious attributes of an email or other threat artifact received by a computing system or network and utilize relational learning to predict the maliciousness of attributes represented by other nodes (of the node graph).

Claim (Index 12):
The method of  claim 11 , further comprising:\n combining the generated node graphs into a composite node graph,\n wherein the composite node graph includes one or more intermediate nodes that join unique instances of an indicator derived from different artifacts received by the computing system.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 1.72727
- Patent Class: 726.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15848337', '15236575', '15236595', '15236582', '16029964']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2567510789894743
- 35 USC 102 Novelty (BERT): 0.4710242478973484
- Combined Prediction Score: 0.2781783958802617
- Mean Citation Score: 148.58066000000005
- Max Citation Score: 151.89603
- Similarity Product: 107.96509850721

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

Dataset: test