Abstract: A computer search service can receive an enterprise graph query from a client computing device that is remote from the computer search service, with the enterprise graph query identifying an actor object set, a target object set, and a relationship between the actor object set and the target object set. The search service can return results of the enterprise graph query to the client device. The search service can receive from the client device an indication of user input instructing the search service to persist the enterprise graph query, with the indication of user input also instructing the search service to associate the persisted enterprise graph query with an entity. Moreover, in response to receiving the indication of user input, the search service can persist the enterprise graph query as well as associate the persisted enterprise graph query with the entity and/or enter a subscription entry for the query.

Abstract: A system, processes, and a computer-readable storage medium are provided method includes receiving a search query including one or more of a textual phrase, a document, or data including metadata from a user. For example, a processor may execute a theme-generating machine learning algorithm to generate a theme of the search query. Profiles of other users are identified as similar to a profile of the user may be located. A search history of each of the located other users may be located in the collected search history. Content in the searchable content that corresponds to the generated theme of the search query and according to a result of the evaluation of the located search history of each of the other users may be obtained. The obtained content may be scored based on a scoring algorithm and output a set of scored search results to the input/output device.

Abstract: The present disclosure relates to methods, systems, and storage media for updating confidence scores of labels based on subsequent electronic activities. Exemplary embodiments may maintain a plurality of node profiles corresponding to a plurality of unique entities; access a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers; identify a first electronic activity to process; assign a tag to the first electronic activity based on the data included in the electronic activity; determine a confidence score of the tag based on the data included in the first electronic activity; identify a second electronic activity to process; and update the confidence score of the tag assigned to the first electronic activity responsive to parsing the second electronic activity.

Abstract: A method of ranking recommendations comprising receiving a recommendation to improve space utilization of a space, retrieving context data associated with the space, the context data including data describing previous user interest in other recommendations related to the recommendation and at least one of: data describing a current space utilization for the space, data describing a number of recommendations that are associated with the space, data describing environmental preferences of first individuals associated with the space or a building including the space, or data describing an organizational grouping of second individuals associated with the space or the building, calculating a score for the recommendation based on the previous user interest and the at least one of: the current space utilization, the number of recommendations, the environmental preferences, or the organizational grouping, and performing an action based on the score using at least one of the score or the recommendation.

Abstract: Methods and systems for managing a project. Project templates can be stored in a project database. At least one start date and/or at least one end date can be accepted for each project template. Information related to accepted project templates can be accepted. A user can access the information related to accepted project templates from a user interface.

Abstract: Some embodiments provide a method for generating a graphical user interface (GUI) for a research system. The method receives a request from a user of the research system for information about a particular category. The method generates a chart that displays a set of events associated with the particular category over a particular period of time. The method incorporates the chart into a GUI for the particular category for transmission to the user. Some embodiments generate a list of events associated with the particular category and generate a GUI that displays the list of the events. Each event is represented in the list by a title of a document identified by the research system as representative of the event.

Abstract: A method comprises receiving a network of a plurality of nodes and a plurality of edges, each of the nodes of the plurality of nodes comprising members representative of at least one subset of initial data points, selecting a subset of the data points based on each node of the plurality of nodes, for each selected data point of the set of selected data points, determining a predetermined number of other data points that are closest in distance to that particular selected data point, grouping the selected data points into a plurality of groups based, at least in part, on the predetermined number of other data points of the set of selected data points that are closest in distance, each group of the plurality of groups including a different subset of data points, and providing a list of selected data points and the plurality of groups.

Abstract: Disclosed are various approaches for managing the status of machine-learning models using distributed ledgers. A registration request for a machine-learning model can be received. The registration request can include a model name for the machine-learning model, a version identifier for the machine-learning model, a network address from which the machine-learning model can be retrieved, a source code hash for a source code version of the machine learning model, and a runtime hash for a binary executable version of the machine-learning model. A registration identifier can then be created based at least in part on the source code hash and the runtime hash. Subsequently, an entry in the distributed ledger can be created for the machine-learning model. The entry can include the registration identifier, the model name, the model version, the network address, the source code hash, and the runtime hash.

Abstract: A system including one or more processors and one or more non-transitory media storing computer instructions configured to run on the one or more processors and perform: identifying a first sub-population of case individuals from a gross population of the case individuals; presenting first test content to a first test sub-population of the case individuals, the first test content is selected according to a first statistical model; measuring a first test sub-population average feedback metric based on first test content feedback provided from the first test sub-population of the case individuals; determining that the first test sub-population average feedback metric exceeds a first control population average feedback metric of a first control population of the case individuals; and determining that a probability value for a difference between the first test sub-population average feedback metric and the first control population average feedback metric is less than a predetermined significance level value.

Abstract: In some embodiments, techniques for searching comprise providing receiving a request for a local search, determining a current location associated with a document currently being viewed, determining a search restriction specification associated with the current location associated with the document currently being viewed, wherein the search restriction specification relates to a specification of a set of pages to be searched, obtaining local search results by performing a search, wherein the local search results are limited to members of the set of pages to be searched in accordance with the search restriction specification, and presenting the local search results.

Abstract: A system and method to provide adaptively re-ranked search results in response to a search query. An initial ranking of search results associated with a search query is established. A query identifier associated with the search query received from an end-user system is identified. Based on the query identifier, a set of model parameters associated with the search query are identified. In response to receiving the search query, using a machine-learning model, a re-ranking of the search results based at least in part on the set of model parameters and the initial ranking of the search results is determined. The re-ranked search results are provided to the end-user system.

Abstract: A method of optimizing an EOU search by increasing the number of sources searched by a predetermined variable and notifying the user of the optimal search results. For example, the EOU tool may search 5-20 pages in 5 page increments and compare the results of the various searches to determine which one provides the best results. Based on the results of the searches the EOU tool can send a notification to the user such as “increasing the search results by 10 pages will improve EOU results”.

Abstract: Provided is a process of obtaining a plurality of location data sets from different providers of user geolocation history, each location data set including a plurality of user-activity records, each user-activity records being associated with a user identifier and including geolocations of the corresponding user and times that the corresponding user was at the geolocations, the different providers having different user identifiers for a given corresponding user; matching, by one or more processors, the user identifiers between the location data sets based on geolocations of the corresponding user and times that the corresponding user was at the geolocations; and storing the matched user identifiers in association with one another in corresponding user profiles.

Abstract: A method for generating a microapp recommendation comprises receiving, at a client computing device, microapp metadata that characterizes multiple microapps. The method further comprises using a resource access application executing at the client computing device to launch a networked application that displays a user interface. The method further comprises calculating a composite correlation score for a particular microapp. The composite correlation score quantifies correlation between functionality provided by the user interface of the networked application and functionality provided by the particular microapp. The method further comprises using the composite correlation score to make a determination with respect to whether the particular microapp should be recommended to a user of the client computing device.

Abstract: An utterance recommendation system may obtain a plurality of utterance influencing attributes influencing a response recommended for a user query from a plurality of sources. The system may collate the utterance influencing attributes to provide enriched user data and may identify a set of preconfigured potential utterance options associated with the user query. The system may implement a plurality of utterance recommendation techniques to analyze the enriched user data based on associated predefined rules, and provide a preferential rank ordering of the preconfigured potential utterance options to be recommended based on the analysis. The system may determine a single optimized rank ordering of the preconfigured potential utterance options representing a ranking order of the preconfigured potential utterance options. The system may provide the response to the user query, based on a potential utterance option ranked highest in the single optimized rank ordering.

Abstract: Disclosed are techniques for trimming large clusters of related records. In one embodiment, a method is disclosed comprising receiving a set of clusters, each cluster in the clusters including a plurality of records. The method extracts an oversized cluster in the set of clusters and performs a breadth-first search (BFS) on the oversized cluster to generate a list of visited records. The method terminates the BFS upon determining that the size of the list of visited records exceeds a maximum size and generates a new cluster from the list of visited records and adding the new cluster to the set of clusters. By recursively performing BFS traverse over the oversized cluster and extracting smaller new clusters from it, the oversized cluster is eventually partitioned into a set of sub-clusters with the size smaller than the predefined threshold.

Abstract: A system and method for generating a column-oriented data structure repository for columns of single data types. The method includes: receiving instructions to generate a new column of a single data type for a first data structure, wherein the first data structure is a column oriented data structure; and storing, based on the instructions, the new column within the column-oriented data structure repository, wherein the column-oriented data structure repository is accessible to at least a second user account.

Abstract: The present invention discloses method and virtual assistance system for determining response to user queries. The virtual assistance system receives data comprising plurality of interaction between one or more users and one or more real agents for resolving query, where data is classified into user and real agent data. Entities and intent identified from each of the classified user data and real agent data are classified using predefined domain model. The entities and intent are combined to identify plurality of sequence of resolution data. Based on classification of entities and intent, virtual assistance system determines first set of resolution data and second set of resolution data. Thereafter, each of plurality of sequence of resolution data is clustered into one or more category associated with type of users, based on first set and second set of resolution data, parameters associated with users and historical resolution data used for responding to query.

Abstract: A method of processing media content in Moving Picture Experts Group (MPEG) Network Based Media Processing (NBMP) is performed by at least one processor, and includes performing a function and function group discovery, wherein wildcard search is enabled in the function and function group discovery, transmitting, to a function repository storing one or more functions for processing the media content, a search query for at least one among the one or more functions, based on the search query being transmitted, receiving, from the function repository, a reply identifying the at least one among the one or more functions and including a rank of the at least one among the one or more functions, and processing the media content, using the identified at least one among the one or more functions in an order based on the included rank of the at least one among the one or more functions.

Abstract: Techniques are presented herein for improved search based on group relevance. The techniques include determining account node groups based on the interactions of accounts with content. When a search query is received from a particular account, the group(s) associated with that account are determined, and the content items determined to be relevant to other accounts in the group(s) are given higher relevance in the search results. In some embodiments, groups are determined using partitioning and/or queries can be rewritten based on the group(s).