Abstract: Methods and systems are described herein for improving anomaly detection in timeseries datasets. Different machine learning models may be trained to process specific types of timeseries data efficiently and accurately. Thus, selecting a proper machine learning model for identifying anomalies in a specific set of timeseries data may greatly improve accuracy and efficiency of anomaly detection. Another way to improve anomaly detection is to process a multitude of timeseries datasets for a time period (e.g., 90 days) to detect anomalies from those timeseries datasets and then correlate those detected anomalies by generating an anomaly timeseries dataset and identifying anomalies within the anomaly timeseries dataset. Yet another way to improve anomaly detection is to divide a dataset into multiple datasets based on a type of anomaly detection requested.

Abstract: Systems, methods, and computer media for visualizing data are provided herein. The described examples allow one-dimensional data visualizations generated using visualization tools and backend components to be displayed in response to a request to view data that includes one or more sets of Cartesian columns. A data visualization request can specify data for inclusion in a data visualization and properties for the visualization, including transpose factors for data sources. The data sources having transpose factors can be cloned to represent respective combinations of the data source with each transpose factor, and then joined to other cloned or non-cloned data sources to generate the resulting one-dimensional visualization.

Abstract: Aspects of the technology evaluate whether a response to a client device search query results in the client device traveling to a location associated with the response (FIG. 1). One or more wireless stations are selected based on the location associated with the search query (604, 606). Wireless station identifiers are sent, along with the search results, to the client device (504, 610). The client device compares the received identifiers against the identifiers of one or more observed wireless stations with which the mobile device is in communication or are otherwise visible (508). Log information is generated by the client device as a result of the comparison (510). The log information is transmitted to the network without user ID or other client-identifiable information included in the log (512). The received log information is then used to accurately evaluate conversions and evaluate search quality, which enhances the user experience and provides for a more efficient search result process (612, 614).

Abstract: Transactions include text fields, such as description fields. Transactions are extracted from financial institutions using web-scraping extraction. In the process of extracting transactions, errors can be introduced into text fields, such as the inclusion of a space within a word or the removal of a space between words. A statistical approach is applied to the text fields. When two alternative text fields are presented, the alternative that statistically includes more common tokens, such as unigrams and bigrams, is chosen as the correct alternative. The incorrect alternative is replaced by the correct alternative in the text field.

Abstract: A method may include selecting a cohort of entities for migration from a source storage repository to a target storage repository, obtaining a mapping between a source storage schema of the source storage repository to a target storage schema of the target storage repository, and migrating data for the entities in the cohort. Migrating the data of an entity may include copying, without locking the data in the source storage repository and in the target storage repository, the data from the source storage repository to the target storage repository, verifying, while the data is locked, that the data in the source storage repository is the same as the data in the target storage repository, changing, while the data in the source storage repository and the target storage repository is locked, an entity pointer for the entity to the target storage repository based on the verifying, and unlocking the data.

Abstract: A service monitoring system (SMS) produces key performance indicator (KPI) scores that indicate the performance of a service. To produce the KPI scores, the SMS may process the data for a large number of machine entities that perform the service. This data can be processed on a per-entity basis to produce a per-entity KPI score representing the contribution of a particular machine to the overall KPI. The per-entity KPI scores can be transformed to statistical representations which can be visualized as a distribution stream graph. The visualization may be presented with interactive aspects. Automatic entity definitions may also be generated based on content derived from the processed data.

Abstract: A system and method for data analysis and presentation of data are provided. The system for data analysis and presentation of data includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to determine a plurality of properties of the plurality of data sets, to analyse a categorical variable of the plurality of data sets based on the plurality of properties of the plurality of the plurality of data sets, to identify one or more custom rules based on an analysed categorical variable, to interpret the identified one or more custom rules, to identify a graph based on one or more custom rules, to identify one or more textual insights based on one or more custom rules and the identified graph, to present the identified graph and one or more textual insights.

Abstract: A method for standardizing data input, data output and data manipulation at a data lake is provided. Methods include receiving a data transfer instruction comprising a seed file. Methods include parsing the seed file. Methods include validating the seed file. Methods include retrieving one or more data elements from one or more data sources as specified in the seed file. Methods include saving the retrieved data elements to a data lake. Methods include archiving the data elements at the data lake. Methods include receiving a schema from a network data mover client at an edge node at the data lake. Methods include creating a table to match the schema and validating the data elements using the schema. Methods include pushing the data elements into the table using the schema. Methods include saving the table that comprises the data elements in a shoreline edge node within the data lake.

Abstract: In an aspect, provided is a method for targeted extraction of data satisfying a query. The method can rely upon one or more data structures indicative of data values satisfying or not satisfying one or more filters. Only the data indicated as satisfying (or as not satisfying) the data in a data structure related to the query are extracted. The extracted data may then be sorted.

Abstract: Systems and methods are provided for efficiently maintaining a transaction sequence witness service to ensure that requests to read data provide consistent results across all storage nodes in a distributed system. When a storage node receives a request for a data object, the node may obtain—from transaction sequence witness service—the latest sequence number associated with the object. If the sequence number indicates the object has been modified in the period of time since the currently stored version was stored, the node can obtain the current version from persistent storage.

Abstract: Various corpora of content objects and other information sources beyond the corpora of content objects are processed to identify personally identifiable information (PII). PII that is associated with a named person is codified into a first portion of a graph-oriented data structure. Also, PII that is associated with an alias that might refer to a named person is codified into a second portion of the graph-oriented data structure. A determination is made that the alias that might refer to a named person is indeed an alias that is a coreference to the named person. Based on that determination then, since the first portion of the graph and the second portion of the graph refer to the same person, then the PII of the second portion of the graph can be deemed to be PII of the same person. PII in common and/or language processing can be used to establish coreferences.

Abstract: One example method includes creating a source FS Merkle tree having a structure that matches a topology of a source FS, and a target FS Merkle tree having a structure that matches a topology of a target FS, receiving a change to the source FS, implementing the change in the source FS, updating the source FS Merkle tree to reflect the change, replicating the change to the target FS so that, with respect to the change, the target FS is synchronized with the source FS, updating the target FS Merkle tree to reflect the change to the target FS, and comparing the source FS Merkle tree to the target FS Merkle tree.

Abstract: A method including receiving a query request sent by a client; determining resource occupation information of a data set corresponding to the query request; if determining, according to the resource occupation information, to cache the query request, then acquiring the data set corresponding to the query request, and storing the data set in an external memory; and reading the data set from the external memory and sending the data set to the client. By using the method, returning multiple data sets to a client within a short period of time is avoided, thus reducing the occupation of CPU resources, memory resources and network resources, avoiding client query timeout or failure, and improving the usage experience of uses.

Abstract: Embodiments for implementing intelligent audio composition guidance for a video by a processor. One or more acoustic characteristics used in a plurality of video segments may be identified, from a corpus, as having similar acoustic, linguistic, and visual characteristics of a selected video segment.

Abstract: Techniques are provided for finding unused vertex and edge identifiers (IDs) in a distributed graph engine. A run-time data structure may be built during the loading of the graph. The data structure identifies unavailable IDs that are associated with graph entities of the graph. The data structure is traversed to determine one or more ranges of free IDs. Unused IDs are generated from the ranges.

Abstract: A method is provided that includes establishing, by an application server, a remote access session with a client device, and creating, by a file system agent running on the application server, a metadata-only virtual file system associated with the remote access session, wherein the virtual file system only comprises file metadata associated with a plurality of files residing in a local file system of the client device. The method further includes responsive to receiving, by the virtual file system, a request to access content of a file referenced by the virtual file system, redirecting the request to a file system driver implementing at least a sub-tree of the local file system of the client device.

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for generating highly scalable temporal graph databases. In one embodiment, a novel architecture is presented that enables the identification of mutation or changes in graphs. For the identification a combination of graph-based modeling and journal entry is used. Events occurring are consumed and changes are ingested, transformed for use by a graph simulation system. The changes are journaled using a vertex centric temporal journaling schema.

Abstract: Techniques are disclosed for storing an arranging data in a database. A method includes a computer system storing, in a database, data indicative of a graph data structure having a plurality of nodes connected by a plurality of edges. The method further includes the computer system determining that a number of edges connected to a first node satisfies a threshold number. In response to the determining, the computer system may store an index in an index row associated with the first node. The index identifies a first row having first and second ranges of values stored in first and second rows, respectively. The values in the first and second rows correspond to edges connected to the first node. The values in the first and second ranges are usable to indicate properties of corresponding ones of the plurality of edges.

Abstract: A method including receiving, by one or more processing circuits, building data, generating, by the one or more processing circuits, a first digital twin based on the building data, wherein a first system stores the first digital twin and a second system stores a second digital twin generated based on the building data, where the first digital twin includes a relationship that forms a connection between the first digital twin and the second digital twin by linking a first entity of the first entities of the first digital twin and a second entity of the second entities of the second digital twin, and performing, by the one or more processing circuits, one or more operations based on at least one of the first digital twin, the second digital twin, or the relationship that forms the connection between the first digital twin and the second digital twin.

Abstract: One example method includes creating a source FS Merkle tree having a structure that matches a topology of a source FS, and a target FS Merkle tree having a structure that matches a topology of a target FS, receiving a change to the source FS, implementing the change in the source FS, updating the source FS Merkle tree to reflect the change, replicating the change to the target FS so that, with respect to the change, the target FS is synchronized with the source FS, updating the target FS Merkle tree to reflect the change to the target FS, and comparing the source FS Merkle tree to the target FS Merkle tree.