Abstract: Systems and methods for managing a plurality of data objects in a bitemporal manner are disclosed. The system includes one or more processors and one or more non-transitory computer-readable media that collectively store instructions that cause the computing system to perform operations, the operations comprising: maintaining a first set of data objects comprising one or more values corresponding to one or more data fields; receiving one or more modifications associated with at least one of the one or more values; modifying at least one of the one or more values as a function of the one or more modifications; constructing a second set of data objects as a function of the modified one or more values; and constructing a third set of data objects as a function of the second set of data objects, wherein the third set of data objects comprises an alternate version of the one or more values.

Abstract: Systems and methods for managing a plurality of data objects in a bitemporal manner are disclosed. The system includes one or more processors and one or more non-transitory computer-readable media that collectively store instructions that cause the computing system to perform operations, the operations comprising: maintaining a first set of data objects comprising one or more values corresponding to one or more data fields; receiving one or more modifications associated with the one or more values; generating token data as function of each modification of the one or more modifications; generating one or more digital tokens as a function of the token data; modifying the one or more values as a function of the one or more modifications; and constructing a second set of data objects as a function of the modified one or more values.

Abstract: In one embodiment, a method includes accessing a document, identifying one or more noun phrases in the document by performing a pre-processing on the accessed document, generating, for each identified noun phrase, a list of candidate entities corresponding to the noun phrase, wherein the list of candidate entities is looked up in an entity index using the noun phrase, computing, for each candidate entity corresponding to each identified noun phrase, a confidence score that the noun phrase is intended to reference the candidate entity by analyzing the accessed document by a machine learning model, constructing a pool of mention-entity pairs for the accessed document, filtering the pool of mention-entity pairs by removing each mention-entity pair from the pool based on their computed confidence scores, and storing the post-filtered pool of mention-entity pairs in a data store in association with the accessed document.

Abstract: Systems and methods are described providing detailed input/output (I/O) metric information that is collected and gathered by an agent of the storage volume. An I/O request is received by a storage volume, and the agent associates primary and secondary identifiers with that I/O request. For example, a trace may be associated with that I/O request. The agent may store this I/O metric information in a ring buffer. Further, after collection and aggregation, statistics may be published by an I/O metric service that further processes the data provided by the agent. Advantageously, interdependent relationships associated with the I/O request or I/O operations of that request may be included in those statistics. This may allow an operator to evaluate the performance of I/O requests for a network.

Abstract: Systems and methods are described for dynamically detecting outliers in a set of input/output (I/O) metrics collected and aggregated by a storage volume network. An I/O request is received by a storage volume network, and an agent of the storage volume network associates primary and secondary identifiers with that I/O request. For example, a trace may be associated with a request to write data to a storage volume network, and spans may be associated with the individual operations required to fulfill that request. Once gathered, I/O metrics may be aggregated based on the associated identifiers. I/O metric information regarding outliers may be received from the storage volume network, processed, and published by an I/O metrics service to identify the outliers among the primary and secondary identifiers. These outliers may then be stored for further analysis, and may be utilized to determine improvements to the performance of a storage volume network.