An apparatus includes a processor. The processor extracts a column from an external source for import into a database configured to store a set of columns including a first and second column. The processor splits the entries of the import column into a set of terms. The processor generates a first, second, and third vector based on the frequency of each term of the set of terms in the first, second, and import columns, respectively. The processor determines a first similarity measure between the first and third vectors and a second similarity measure between the second and third vectors. The first similarity measure is greater than the second. In response, the processor provides an indication to a user that the first column is a mapping candidate for the import column, such that entries of the import column may be stored in the database as additional entries in the first column.

Systems and methods of the present disclosure are directed to defining a data store format for storing state information related to border-gateway protocol (BGP) routing information base (RIB) entries, BGP Neighbor Tables, intermediate system-intermediate system (IS-IS) adjacencies, Link-State Databases, Interface information, Chassis information, etc in a binary format. A brick data store (BDS) system can define tables, table properties, objects and attributes for an application in the system using configuration files expressed in Java Script Object Notation (JSON). The data format can be uniform across inter-process communication, file and in-memory representation.

Systems, methods, and non-transitory computer-readable media can provide an abstraction layer capable of accessing one or more data sources. A set of data can be acquired, via the abstraction layer, from the one or more data sources. The set of data can be searched, based on a query acquired via a data processing environment, to produce resulting data. At least some of the resulting data can be utilized to perform one or more data operations via the data processing environment.

A content unification system is described herein that aligns related content from various sources into one unified stream. The system leverages tagging (e.g., hashtags or other added metadata associated with content) to filter and connect related content across sites, formats, and sources. One component of the system is a user-friendly and customizable “dash board” view of the various topics, called a “tagboard”. Tagboards can be quickly and easily created by users and can be embedded on any website. Users can interact with various content sources such as blogs, forums, or services without leaving the tagboard they are viewing. The content unification system provides users the tools to make the web efficient, increase user interaction, and increase the signal to noise ratio. The system also allows site owners and publishers to monetize their traffic better by directing advertisements to their content in real time.

The present disclosure relates to systems and methods for an intelligent assistant (e.g., a chatbot) that can be used to enable a user to generate a machine learning system. Techniques can be used to automatically generate a machine learning system to assist a user. In some cases, the user may not be a software developer and may have little or no experience in either machine learning techniques or software programming. In some embodiments, a user can interact with an intelligent assistant. The interaction can be aural, textual, or through a graphical user interface. The chatbot can translate natural language inputs into a structural representation of a machine learning solution using an ontology. In this way, a user can work with artificial intelligence without being a data scientist to develop, train, refine, and compile machine learning models as stand-alone executable code.

A system and method are provided for automatically proofing the patent specification of a granted patent issued on a patent application. The method comprises the steps of scanning amendments made to the patent application during prosecution; assembling the most recent claims, based on the scanned amendments, to create a test claim set of the claims; comparing the test claim set to the claims of the issued patent as published; and identifying any differences between the compared sets of claims and communicating the differences to a user.

A method includes storing a parameter related to a user, storing descriptive data for multiple identifiers, and indexing multiple events. Each event corresponds to a physical object supplied to a user on behalf of an entity. The method includes identifying a first set of identifiers based on commonality among the descriptive data. The method includes training a machine learning model for the first set of identifiers based on event data from within a predetermined epoch. The method includes receiving an indication of a selected identifier and determining a first intake metric of the selected identifiers using the machine learning model. The method includes determining a second intake metric of the selected identifier and the parameter and transforming the user interface according to the first and second intake metrics. The first intake metric represents an amount of resources expected to be received during a second epoch subsequent to the predetermined epoch.

In some embodiments, the present disclosure provides for an exemplary computer-implemented system that may include a longitudinal data engine, including: a processor and specialized index generation software to generate: an index data structure for a respective event type associated with each respective subject or object; where each respective index data structure is a respective event type-specific data schema, defining how to store events of a particular event type to form longitudinal data of each respective subject or object; an ontology data structure that is configured to describe one or more properties of a respective event of a respective subject or object; and longitudinal data extraction software to extract a respective longitudinal data for a plurality of index data structures and a plurality of ontology data structures associated with a plurality of subjects or objects.

The systems and methods described herein provide highly dynamic and interactive data analysis user interfaces which enable the data analyst to quickly and efficiently explore large volume data sources, such as computer code or intellectual system. A user interface can be implanted that includes a plurality of nodes associated with portions of a process. The nodes may include indications of logical relationships between nodes. Node identifiers may be associated with particular nodes and be usable to select particular nodes. Reliability scores associated with particular nodes can be included.

A method, system, and medium for automated analysis of business intelligence each: receive natural language input from a user; evaluate, via a natural language understanding processor that includes a parser and an interpreter, the natural language input to determine an intent of the user; determine the intent of the user and generate a query based on a context manager; send an identification of the failure to a failure analysis system for human intervened analysis and refinement of a natural language model used by the natural language understand processor; assess, via a context manager processor, to determine a user interest in one or more portions of results of the query, a scrolling of the user through the results of the query; and refine, based on the user interest in the one or more portions of the results of the query, an output of the results of the query.