Systems, Methods, and Devices to Determine Claim Event Data

1 . A method, comprising:

determining a plurality of optimized weight values for claim data stored in at least one memory, wherein the claim data comprises item data, geolocation data, liability data, user data, or combinations thereof;

receiving search input data provided to a search engine via a user device, wherein the search engine is configured to search the at least one memory;

determining claim event data based on the plurality of optimized weight values, the claim data, and the search input data, wherein the determined claim event data corresponds to one or more legal claims associated with the search input data; and

transmitting the determined claim event data to the user device, wherein the user device is configured to display information relating to the determined claim event data.

2 . The method of claim 1 , wherein determining the plurality of optimized weight values for the claim data comprises training one or more machine learning models based on the claim data to determine the plurality of optimized weight values using iterative feedback based on the claim data.

3 . The method of claim 2 , wherein training the one or more machine learning models to determine the plurality of optimized weight values using iterative feedback comprises:

determining a plurality of expected values for the claim data, wherein a respective expected value corresponds to an expected utility of a respective claim datum with respect to the one or more legal claims;

determining a plurality of standard deviation values for the claim data based on the plurality of expected values;

determining a plurality of ratios for the claim data based on the plurality of expected values and the plurality of standard deviation values; and

determining the plurality of optimized weight values for the claim data based on the plurality of ratios.

4 . The method of claim 3 , wherein determining the plurality of ratios comprises:

determining a plurality of opportunity sets based on the claim data, wherein a respective opportunity set corresponds to a plurality of candidate weight values for a respective subset of claim data; and

determining the plurality of ratios based on the plurality of opportunity sets, the plurality of expected values, and the plurality of standard deviation values, wherein a respective ratio corresponds to a ratio of a respective expected value and a respective standard deviation value for the respective opportunity set.

5 . The method of claim 4 , wherein determining the plurality of optimized weight values based on the plurality of ratios comprises:

determining a ranking of the plurality of ratios;

determining an optimized ratio of the plurality of ratios based on the ranking;

determining an optimized opportunity set of the plurality of opportunity sets based on the optimized ratio; and

determining the plurality of optimized weight values for the claim data based on the optimized opportunity set, wherein the plurality of optimized weight values corresponds to a respective subset of the plurality of candidate weight values for the optimized opportunity set.

6 . The method of claim 5 , wherein determining the plurality of optimized weight values for the claim data based on the optimized opportunity set comprises determining the plurality of optimized weight values using the iterative feedback based on the claim data and updated claim data stored in the at least one memory, wherein the iterative feedback corresponds to neural network feedback.

7 . The method of claim 2 , wherein determining the claim event data based on the plurality of optimized weight values, the claim data, and the search input data comprises:

using the one or more trained machine learning models to determine the claim event data based on the plurality of optimized weight values, the claim data, and the search input data.

8 . The method of claim 2 , wherein:

the one or more machine learning models are configured to use linear and non-linear optimization systems, wherein the linear and non-linear optimization systems comprise one or more vector maximization and minimization equations;

the one or more machine learning models comprise one or more neural networks, one or more linear regression models, one or more logistic regression models, one or more linear discriminant analysis models, one or more classification or regression tree models, one or more naïve Bayes models, one or more learning vector quantization models, one or more posterior density function models, one or more independent stochastic regressor models, one or more general stochastic regression models, one or more general non-linear hypothesis models, or combinations thereof; or

combinations thereof.

9 . The method of claim 1 , wherein the claim data further comprises accident data, biomarker data, transaction data, chemical drug data, food data, implant data, scientific data, satellite data, supply chain data, cellular data, sensor data, court document data, Internet-of-Things data, device data, litigation cost data, litigation payout data, claim expected value data, legal recovery data, crime data, traffic data, navigation data, audio data, video data, photo data, weather data, health care records data, billing data, purchase history data, commodities data, time duration data, real-time data, emissions data, pollution data, or combinations thereof.

10 . The method of claim 1 , wherein:

the at least one memory comprises one or more distributed ledgers;

the claim data comprises augmented data, wherein the augmented data comprises data generated based on at least a portion of the item data, the geolocation data, the liability data, the user data, or combinations thereof; or

combinations thereof.

11 . The method of claim 1 , wherein the one or more legal claims comprise one or more litigation claims, one or more false advertising claims, one or more Medicare secondary payer claims, one or more automobile injury claims, one or more opioid claims, one or more products liability claims, one or more personal injury claims, one or more patent infringement claims, one or more workers' compensation claims, one or more commercial litigation claims, one or more breach of contract claims, one or more breach of warranty claims, one or more libel claims, one or more slander claims, one or more nuisance claims, one or more debt collection claims, one or more malpractice claims, one or more property damage claims, one or more class action claims, one or more tort claims, one or more negligence claims, or combinations thereof.

12 . The method of claim 1 , wherein receiving the search input data provided to the search engine via the user device comprises:

generating the search engine for the at least one memory;

providing a search interface for the search engine to the user device, wherein the search interface is configured to be displayed by the user device; and

receiving the search input data provided to the search interface via the user device.

13 . The method of claim 1 , wherein the user device is configured to display the information relating to the determined claim event data using a results interface of the user device.

14 . A method, comprising:

receiving search input data provided to a search engine via a user device, wherein the search engine is configured to search at least one memory configured to store claim data, wherein the claim data comprises item data, geolocation data, liability data, user data, or combinations thereof;

determining claim event data based on the claim data, the search input data, and a plurality of optimized weight values determined for the claim data, wherein the determined claim event data corresponds to one or more legal claims associated with the search input data; and

transmitting the determined claim event data to the user device, wherein the user device is configured to display information relating to the determined claim event data.

15 . The method of claim 14 , wherein the plurality of optimized weight values were previously determined using iterative feedback by training one or more machine learning models based on the claim data.

16 . The method of claim 15 , wherein determining the claim event data based on the claim data, the search input data, and the plurality of optimized weight values comprises:

using the one or more trained machine learning models to determine the claim event data based on the plurality of optimized weight values, the claim data, and the search input data.

17 . The method of claim 14 , wherein the claim data further comprises accident data, biomarker data, transaction data, chemical drug data, food data, implant data, scientific data, satellite data, supply chain data, cellular data, sensor data, court document data, Internet-of-Things data, device data, litigation cost data, litigation payout data, claim expected value data, legal recovery data, crime data, traffic data, navigation data, audio data, video data, photo data, weather data, health care records data, billing data, purchase history data, commodities data, time duration data, real-time data, emissions data, pollution data, or combinations thereof.

18 . The method of claim 14 , wherein the one or more legal claims comprise one or more litigation claims, one or more false advertising claims, one or more Medicare secondary payer claims, one or more automobile injury claims, one or more opioid claims, one or more products liability claims, one or more personal injury claims, one or more patent infringement claims, one or more workers' compensation claims, one or more commercial litigation claims, one or more breach of contract claims, one or more breach of warranty claims, one or more libel claims, one or more slander claims, one or more nuisance claims, one or more debt collection claims, one or more malpractice claims, one or more property damage claims, one or more class action claims, one or more tort claims, one or more negligence claims, or combinations thereof.

19 . The method of claim 14 , wherein receiving the search input data provided to the search engine via the user device comprises:

generating the search engine for the at least one memory;

providing a search interface for the search engine to the user device, wherein the search interface is configured to be displayed by the user device; and

receiving the search input data provided to the search interface via the user device.

20 . A computing system, comprising:

one or more processors; and

at least one memory comprising a plurality of program instructions which, when executed by the one or more processors, cause the one or more processors to:

determine a plurality of optimized weight values for claim data stored in the at least one memory, wherein the claim data comprises item data, geolocation data, liability data, user data, or combinations thereof;

receive search input data provided to a search engine via a user device, wherein the search engine is configured to search the at least one memory;

determine claim event data based on the plurality of optimized weight values, the claim data, and the search input data, wherein the determined claim event data corresponds to one or more legal claims associated with the search input data; and

transmit the determined claim event data to the user device, wherein the user device is configured to display information relating to the determined claim event data.