CROSS-REFERENCE TO RELATED APPLICATIONS

applicationSer. No.Date FiledTitleCurrentHerewithAUTOMATED SCALABLEapplicationCONTEXTUAL DATA COLLECTIONAND EXTRACTION SYSTEMIs a continuation of:16/919,231Jul. 2, 2020AUTOMATED SCALABLECONTEXTUAL DATA COLLECTIONAND EXTRACTION SYSTEMwhich is a continuation of:15/905,041Feb. 26, 2018AUTOMATED SCALABLEPatentIssue DateCONTEXTUAL DATA COLLECTION10,706,063Jul. 7, 2020AND EXTRACTION SYSTEMwhich is a continuation-in-part of:15/237,625Aug. 15, 2016DETECTION MITIGATION ANDPatentIssue DateREMEDIATION OF CYBERATTACKS10,248,910Apr. 2, 2019EMPLOYING AN ADVANCED CYBER-DECISION PLATFORMwhich is a continuation-in-part of:15/206,195Jul. 8, 2016ACCURATE AND DETAILEDMODELING OF SYSTEMS WITHLARGE COMPLEX DATASETS USINGA DISTRIBUTED SIMULATIONENGINEwhich is a continuation-in-part of:15/186,453Jun. 18, 2016SYSTEM FOR AUTOMATED CAPTUREAND ANALYSIS OF BUSINESSINFORMATION FOR RELIABLEBUSINESS VENTURE OUTCOMEPREDICTIONwhich is a continuation-in-part of:15/166,158May 26, 2016SYSTEM FOR AUTOMATED CAPTUREAND ANALYSIS OF BUSINESSINFORMATION FOR SECURITY ANDCLIENT-FACING INFRASTRUCTURERELIABILITYwhich is a continuation-in-part of:15/141,752Apr. 28, 2016SYSTEM FOR FULLY INTEGRATEDCAPTURE, AND ANALYSIS OFBUSINESS INFORMATION RESULTINGIN PREDICTIVE DECISION MAKINGAND SIMULATIONwhich is a continuation-in-part of:15/091,563Apr. 5, 2016SYSTEM FOR CAPTURE, ANALYSISPatentIssue DateAND STORAGE OF TIME SERIES10,204,147Feb. 12, 2019DATA FROM SENSORS WITHHETEROGENEOUS REPORTINTERVAL PROFILESand is also a continuation-in-part of:14/986,536Dec. 31, 2015DISTRIBUTED SYSTEM FOR LARGEPatentIssue DateVOLUME DEEP WEB DATA10,210,255Feb. 19, 2019EXTRACTIONand is also a continuation-in-part of:14/925,974Oct. 28, 2015RAPID PREDICTIVE ANALYSIS OFVERY LARGE DATA SETS USING THEDISTRIBUTED COMPUTATIONALGRAPHthe entire specification of each of which is incorporated herein by reference.

BACKGROUND OF THE INVENTION

Field of the Invention

The disclosure relates to the field of automated data extraction, particularly to extraction of data from richly formatted data across different modalities while preserving the context of the data.

Discussion of the State of the Art

Richly formatted data continues to pose a problem to the field of machine learning. While unstructured text may be analyzed using natural language processing models without heeding to the overall structure of the body of text, the structure and layout of richly formatted text may be as important to the context as the content itself. Another problem encountered when processing richly formatted data with machine learning is the multimodal nature of the data, for example, images, audio, and video may exist as supplementary data.

What is needed is a system that can take gather multimodal data, whether it is richly formatted data or unstructured data, and process the gathered data, all the while preserving the context of the data source that may be inherent in its formatting or its type.

SUMMARY OF THE INVENTION

Accordingly, the inventor has conceived, and reduced to practice, a system and method for automated scalable contextual data collection and extraction.

In a typical embodiment, a contextual data collection and extraction is provided that accesses a plurality of richly formatted data sources, and extracts information based on user-provided context. The system may be configured to work across different modalities, and may even cross-reference information from the different modalities to supplement and enrich data extracted from other modalities. The system may also be configured to store extracted data as data, which may be utilized to analyze phase transitions. In addition to enriching a knowledge base for reference purposes, the system may also collectively analyze the data from multiple sources in context, and act as a Data Loss Prevention monitor to ensure that no data leakage has occurred, that may not have been obvious from singly evaluating the data sources.

In one aspect of the invention, a system for contextual data collection and extraction is provided, comprising an extraction engine comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to: receive a context target from a user for desired information to extract, connect to a data source providing a richly formatted dataset, retrieve the richly formatted dataset, process the richly formatted dataset and extract information from a plurality of linguistic modalities within the richly formatted dataset relating at least in part to the context provided by the user, and transform the extracted data into a graph and time series-based dataset; and a knowledge base construction service comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to retrieve the graph and time series-based dataset, create a knowledge base for storing the graph and time series-based dataset, and store the knowledge base in a data store for later reference.

In another embodiment of the invention, a previously created knowledge base is retrieved to store newly extracted information. In another embodiment of the invention, data extracted from a first modality is be used to augment data in a second modality.

In another embodiment of the invention, the system further comprises a proxy connection service comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to determine that an intermediate proxy connection is required based at least in part on connection status in connecting to a data source. In another embodiment of the invention, the proxy connection service determines an optimal proxy network to use as the intermediate proxy connection based at least on successfully connecting to a target data source.

In another embodiment of the invention, a data marker in labeled data is used by the system to identify and label previously unlabeled similar data. In another embodiment of the invention, the system further comprises a phase transition analyzer comprising a proxy connection service comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to: retrieve a knowledge base from the data store, and perform a plurality of graph analysis and transformations on the knowledge base to identify data transitions over time. In another embodiment of the invention, a previously created knowledge base is monitored for unwanted data exfiltration.

In another aspect of the invention, a method for contextual data collection and extraction, comprising the steps of: (a) receiving a context target from a user for desired information to extract, using a extraction engine; (b) connecting to a data source providing a richly formatted dataset, using the extraction engine; (c) retrieving the richly formatted dataset, using the extraction engine; (d) processing the richly formatted dataset and extract information from a plurality of linguistic modalities within the richly formatted dataset relating at least in part to the context provided by the user, using the extraction engine; (e) transforming the extracted data into a graph and time series-based dataset, using the extraction engine; (f) retrieving the graph and time series-based dataset, using a knowledge base construction service; (g) creating a knowledge base for storing the graph and time series-based dataset, using the knowledge base construction service; and (h) storing the knowledge base in a data store for later reference, using the knowledge base construction service.

