PATENT CLAIM ANALYSIS

Application Number: 16029052
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2020-01
Patent Classification: ["706", "012000"]

Abstract:
Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons. Any ML algorithm can use, or operate in conjunction with, a neural knowledge artifactory comprising the knowledge neurons to enhance or improve baseline accuracy, for example during a cold start period, for augmented decision making and/or for labeling data points or establishing ground truth to perform supervised learning.

Claim (Index 1):
A computer-implemented method comprising:\n deploying one or more search engines to search in documents retrieved from a plurality of web-based data sources for, based on one or more domain keywords, a domain knowledge dataset comprising a plurality of domain knowledge data instances, each domain knowledge data instance in the plurality of domain knowledge data instances comprising a plurality of property values for a plurality of properties, each property value in the plurality of property values corresponding to a respective property in the plurality of properties; using the plurality of domain knowledge data instances in the domain knowledge dataset to determine a plurality of combinations of frequently cooccurring properties by learning, from the domain knowledge dataset in the documents retrieved from the plurality of web-based data source, through machine learning with a machine learning model implemented by a computing device, each combination of frequently cooccurring properties in the plurality of combinations of frequently cooccurring properties representing a different combination of properties in a set of all combination of properties generating from the plurality of properties wherein each property in each such combination of frequently cooccurring properties has a support computed from frequencies of occurrences in the plurality of domain knowledge data instances, wherein each such property exceeds a minimum support threshold; selecting, based on one or more artifact significance score thresholds, a specific combination of frequently cooccurring properties from among the plurality of combinations of frequently cooccurring properties; storing the selected specific combination of frequently cooccurring properties as a knowledge artifact in a knowledge neuron; and causing the knowledge neuron to be used by a query processor in one or more computer devices to generate responses to query requests from client computing devices.

Metadata:
- Claim Count in Document: 39.0
- Percentile: 95.0
- Lexical Diversity: 1.85393
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16029032', '16029087', '14456985', '14985557', '14796838']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3204597546782815
- 35 USC 102 Novelty (BERT): 0.510161258818329
- Combined Prediction Score: 0.3394299050922862
- Mean Citation Score: 192.8354468
- Max Citation Score: 284.632
- Similarity Product: 197.98317452049253

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