Abstract: An analysis application utilizes interactivity signals to generate relationships and promote content. One or more interactivity applications, such as a social networking application, are queried to retrieve interactivity signals. Interactivity signals include an interaction pattern that indicates a relationship between a user and relations of the user. A relationship graph is constructed based on the interactivity signals. Content associated with a user is promoted based on the relationship graph. A weight of the interactivity signals is adjusted to improve a ranking of the relationship graph and a ranking of the content.

Abstract: An analysis application utilizes interactivity signals to generate relationships and promote content. One or more interactivity applications, such as a social networking application, are queried to retrieve interactivity signals. Interactivity signals include an interaction pattern that indicates a relationship between a user and relations of the user. A relationship graph is constructed based on the interactivity signals. Content associated with a user is promoted based on the relationship graph. A weight of the interactivity signals is adjusted to improve a ranking of the relationship graph and a ranking of the content.

Abstract: Various aspects provide for implementation of a cloud service for running, monitoring, and maintaining cloud distributed database deployments and in particular examples, provides cloud based services to run, monitor and maintain deployments of the known MongoDB database. Various embodiments provide services, interfaces, and manage provisioning of dedicated servers for the distributed database instances (e.g., MongoDB instances). Further aspects, including providing a database as a cloud service that eliminates the design challenges associated with many distributed database implementations, while allowing the client's input on configuration choices in building the database. In some implementations, clients can simply identity a number of database nodes, capability of the nodes, and within minutes have a fully functioning, scalable, replicated, and secure distributed database in the cloud.

Abstract: An item query can be received on a website that manages a diverse set of items. If the query is associated with a custom taxonomy, the custom taxonomy for the item (or item class) is used to create a user interface with navigational elements generated from the custom taxonomy. The custom taxonomy can be generated from a third-party site that is associated with the item (e.g., a manufacturer). The generated user interface allows users to more readily navigate items from the item class.

Abstract: Disclosed herein are system, method, and computer program product embodiments for displaying object pages containing data displayed in tables in a client application. The client application may provide a user experience framework via which an administrator may pre-configure the behavior of object pages that display data related to the application in table form. A table may be configured to display using lazy loading, tab navigation, or a preview version to list report based on the nature and expected size of the table. When preview version to list report is chosen, a preview version of a table may be provided to a user to allow the user to interact with the data without displaying the entirety of the dataset.

Abstract: The invention relates to a computer-implemented method for classifying a set of data values. For each of the data values of the set of data values, a set of one or more terms associated with the respective data value is determined using one or more first knowledge bases. A set of common terms is determined. The set of common terms comprises terms present in more than one of the sets of terms. For each of the common terms, a number of hits for a lookup query against one or more second knowledge data bases is determined. One or more common terms of the set of common terms with the smallest number of hits are determined and a result is returned. The result comprises the one or more common terms with the smallest number of hits as one or more candidate classes for classifying the set of data values.

Abstract: A source worker node at a source site fetches a task from a message queue. The task specifies replicating a first object at the source site to a destination site. A request for a connection is issued from the source worker node to the destination site. The request is received by a load balancer at the destination site and assigned to a destination worker node. A connection is established between the source and destination worker nodes. A determination is made that the destination site does not include an object that is the same as the first object. Upon the determination, a deduplication is performed between the source and destination worker nodes of segments into which the first object has been divided. Deduplicated segments of the first object are transmitted from the source worker node to the destination worker node for storage at the destination site.

Abstract: One embodiment of the present invention sets forth a method of selecting an entry in a database in an in-vehicle infotainment system. The method includes receiving a second single-character input after receiving a first single-character input, generating a multi-character search string in which the first character of the multi-character search string is the first single-character input and the second character of the multi-character search string is the second single-character input, searching a database stored in the in-vehicle infotainment system for entries that match the multi-character search string, and causing a number of entries that match the multi-character search string to be displayed by the in-vehicle infotainment system. An advantage of the disclosed embodiment is that a vehicle operator can effectively search through a large number of entries in an in-vehicle system with reduced distraction and without stopping the vehicle.

Abstract: Methods and apparatus, including computer program products, are provided for transporting processes within a distributed computing system, such as a cluster. In one aspect, the computer-implemented method may receive an event at a first node. The event may correspond to a process instance for handling the received event. The process instance may be transported from a second node to the first node. The process instance may be transported from a persistence when the process instance is inactive and, when the process instance is active, the process instance may be persisted to enable transport to the first node. Related apparatus, systems, methods, and articles are also described.

Abstract: One embodiment is related to a method for restoring an inode based backup to a path based structure, comprising: receiving a path to be restored; determining one or more selected inodes, wherein metadata associated with the one or more selected inodes is to be used in the restoration; generating a sendmap structure that is indicative of the selected inodes; restoring a first file; and determining whether an inode number of the first file, which identifies an inode of the first file, and its associated metadata are available in a metadata cache, and if so: using the inode number of the first file and its associated metadata in the metadata cache in the restoration of the first file.

Abstract: The techniques described herein provide tools that summarize a dataset by creating a final set of segments that, when visually presented via a histogram or other data presentation tool, show the distribution of at least a portion of the data. To create the final set of segments, the techniques described herein may collect or receive a dataset with distinct values, and divide the dataset into a number of segments that is less than or equal to a segment presentation threshold (e.g., ten segments). After creating the final set of segments, the techniques may configure and/or present data visualizations, such as histograms, for the created segments so that an observer is provided with a good viewing experience.

Abstract: The methods, apparatuses, and systems described herein are designed to analyze comments provided by a coach relating to an agent's interaction with a customer. The methods include receiving a coaching comment regarding an agent's interaction with a customer, applying at least one scoring algorithm to the comment, and outputting a score of the scoring algorithm.

Abstract: In an example, a piece of content is obtained. The piece of content is segmented into a plurality of segments. Each of the plurality of segments is divided into a plurality of units. Then, for each of the plurality of units for each segment, a quality model is used to pass the unit through a long short-term memory (LSTM) corresponding to the unit, causing an embedding of the unit and generating one or more parameters. For each of the plurality of segments for the piece of content, the quality model is used to pass the segment, and one or more parameters obtained from LSTMs corresponding to units within the segment, through an LSTM corresponding to the segment, causing an embedding of the segment. The piece of content is then classified as spam based on the embeddings of the plurality of segments for the piece of content, using the quality model.

Abstract: To leverage the attributes of object storage for applications/systems created to interface with a network files system, an object storage backed file system can accept the defined file system commands from the applications/systems and transform the file system commands into requests that target object storage. The file system is “backed” by object storage because attributes and content of file system entities are stored in objects. For instance, content data and metadata of a file are stored in objects in object storage. This object storage backed file system can be considered a bridge between a client perceived hierarchical file system namespace and a flat namespace of an object storage.

Abstract: An apparatus in one embodiment comprises at least one processing platform including a plurality of processing devices. The processing platform is configured to receive a request to execute an application in a function-as-a-service (“FaaS”) environment, to initiate execution of the application responsive to the request, and to invoke a plurality of application functions with each such application function interacting with one or more backend services in executing the application. The processing platform is further configured to automatically generate an application manifest characterizing relationships between the application functions and the backend services utilized in executing the application, to capture state of the application for a particular point in time based at least in part on the application manifest, and to perform operational recovery of the application for the particular point in time utilizing the captured state.

Abstract: In general, the invention relates to a method for servicing query requests. The method includes determining, by a first query node and in response to a first query request, a user data sub-region and a target sub-region associated with the first query request. The further includes identifying a first input sub-region of the target sub-region using a data flow graph, identifying a second query node associated with the first input sub-region, and issuing a second query request to the second query node to obtain data associated with the first input sub-region. The method further includes receiving, in response to the second query request, a second query result from the second query node, generating a first query result for the target sub-region using at least the second query result, and providing the first query result to an entity associated with the issuance of the first query request.

Abstract: Examples of the present disclosure describe systems and methods of personalizing natural language systems. In aspects, personal data may be uploaded to a personalization server. Upon receiving a data request, a server device may query the personalization server using a user's login information. The login data and the associated personal data may be paired and provided to the personalization server. The paired data may then be provided to a language understanding model to generate a response to the data request. The data in the response may be used to train the language understanding model.

Abstract: A method for detecting software installed on a computer may be provided. The method may comprise obtaining a default user identifier, collecting an installed user identifier, performing an identifier comparison by comparing the installed user identifier with the default user identifier and determining whether an installed user identifier matches a default user identifier, assigning a probability value based on the identifier comparison, performing a threshold comparison of the probability value to the a predetermined threshold value, determining whether the probability value exceeds the threshold value, and in response to determining that the probability value exceeds the threshold value, concluding that the software has been installed on the computer system.

Abstract: A method for accessing information. A request to change a piece of the information is received from a source. A branch for the piece of the information is identified using an identifier in the request. The branch is part of branches in a hierarchical structure and the branches are versions of the piece of the information. The identifier identifies the branch. The branch is changed when the request is from a source that controls a portion of the information in which the branches for the piece of the information are located in a location and the source is part of sources that control portions of the information in the location.

Abstract: A data management device includes a persistent storage and a processor. The persistent storage includes meta-data of data stored in a long term retention (LTR) storage. The processor obtains a file storage request for a file and deduplicates the file against segments stored in the LTR storage while performing garbage collection on the LTR storage. Performing garbage collection includes deleting segments of the data stored in the LTR storage using the meta-data. The meta-data is not stored in the LTR storage.