Abstract: Methods, systems, and techniques for enhancing a VMS are disclosed. One of the disclosed methods includes populating a user interface page with one or more images, each showing a single person matched to a known identity, and each taken contemporaneously with one or more respective access control event occurrences identifiable to the single person. User selection input is receivable to mark at least one of the images as a reference image for an appearance search to find additional images of the single person captured by video cameras within a surveillance system.

Abstract: A method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a combination of a generative and a predictive model, training a phenotype prediction model based on experiential genotype vectors, training a genotype generation model based on sample genotype vectors, generating new genotype vectors, applying the phenotype prediction model to the new genotype vectors to generate scores, determining result genotypes based on a ranking of the available genotypes according to the scores, and generating a result based on the result genotypes, the result indicating one or more genetic constructs for testing.

Abstract: Methods and systems for intelligently recommending selections for a selector control are disclosed. The method includes receiving a recommendation request from a selector control client, the recommendation request comprising a search string and a unique identifier of a user interacting with a selector control; identifying user identifiers of usernames matching the search string; retrieving machine learning features corresponding to the user identifiers of usernames matching the search string; applying a machine learning model to the retrieved machine learning features to assign weights to the retrieved machine learning features; computing recommendation scores for the user identifiers based on the assigned weights to the retrieved machine learning features; ranking the user identifiers based on the recommendation scores; and forwarding a ranked list of user identifiers to the selector control client for displaying in the selector control for selection by the user interacting with the selector control.

Abstract: Systems, methods, and software of processing a tabular dataset. In one embodiment, a system extracts raw association rules from the tabular dataset. Each of the raw association rules comprises a relationship between a set of antecedents and a single consequent, and corresponds to one or more transactions. The system determines potential rule merge groups of the raw association rules based on the antecedents, and determines one or more actual rule merge groups of the raw association rules in each potential rule merge group based on the transactions. The system combines the raw association rules in an actual rule merge group to generate a merged association rule. The system then generates a set of insights based on one or more merged association rules, and performs an operation based on the set of insights.

Abstract: Various embodiments include a method for processing a data set comprising: obtaining a measurement dataset; applying a preprocessing algorithm to the measurement dataset to obtain a preprocessed measurement dataset; applying a classification algorithm to the preprocessed measurement dataset to classify a feature represented by the measurement dataset; determining a quality of the classification of the feature; and adjusting the preprocessing algorithm based on the determined quality. Adjusting the preprocessing algorithm comprises applying a selection algorithm. The selection algorithm describes the change in a value of a parameter of the preprocessing algorithm depending on the determined quality. The preprocessing algorithm comprises at least one of the following operations applied to the measurement dataset: binning; differentiation; integration; and forming tuples having a predetermined relationship from the measurement dataset.

Abstract: The present invention is related to a method for providing dynamic indexer discovery. The method comprises receiving, from an index manager, a status indication associated with a plurality of indexers, wherein each of the plurality of indexers indexes events of raw machine-generated data received from a plurality of data collectors. The method further comprises determining a weight associated with each of the plurality of indexers and selecting an indexer from the plurality of indexers. Subsequently, the method comprises allocating data to the indexer in accordance with a respective weight assigned to the indexer and transmitting the allocated data to the indexer.

Abstract: A method, system and computer-usable medium for performing a streaming scoring operation, comprising: receiving a stream of events, the stream of events comprising a plurality of events; ingesting the plurality of events; extracting features from the plurality of events to provide extracted features; and, generating a streaming scoring value based upon the extracted features.

Abstract: Systems and method that restore application data stored by a virtual machine database for an application (e.g., SQL, SharePoint, Exchange, and so on) running on the virtual machine are described. The systems and methods create an integrated snapshot of the application data stored in the virtual machine database, by creating a secondary copy of the application data stored in the virtual machine database, performing, via a virtual server agent (VSA), a software snapshot of the virtual machine, and performing, via the virtual server agent, a hardware snapshot of the software snapshot of the virtual machine.

Abstract: A system for arranging and displaying guided recommendations via a graphical user interface based on biological extraction, the system comprising a computing device configured to receive, from a wearable device located at a user, at least a biological extraction and at least a datum of user activity data, classify the biological extraction and the at least a datum of user activity as a function of at least a datum of a user fingerprint, select at least a compatible element as a function of the training data and the user fingerprint, wherein the compatible element comprises a guided recommendation, and generate a representation via a graphical user interface of the compatible element.

Abstract: Provided are techniques for data analysis and rule generation for providing a recommendation. Current features are identified from data in a corpus. In response to receiving an indication that the data has changed, a new feature is identified. A feature set is created by identifying one or more related features of the current features. A feature worthiness score for the feature set is generated. In response to the feature worthiness score exceeding a threshold, the feature set is input to a model. One or more rules from the model are received, where each of the one or more rules includes the one or more related features, the new feature, and a recommendation. In response to receiving a set of values for the one or more related features and the new feature, a rule of the one or more rules is applied to provide the recommendation for that set of values.

Abstract: Methods and systems for recommending files to users are described herein. Files may be recommended to a user within a file sharing service. A recommender system may intelligently recommend files to users according to their preferences through machine learning. In addition, a recommender system may recommend files based on what is popular within a group to which the user belongs. The recommendations may be adjusted based on user interaction with one or more recommended files.

Abstract: An illustrative “open archive” architecture provides streamlined access to production data, which originally was stored on a NAS device but which is archived to secondary storage to free up NAS space. An open-archive server coordinates with an open-archive layer on the NAS device. The open-archive server identifies data sets on the NAS that meet archiving criteria, which are then automatically moved to an open archive in secondary storage. The open archive layer intercepts data-access calls coming into the NAS device, and reports the intercepted calls to the open-archive server. If the open-archive server determines that the data referenced in an intercepted call is in the open archive, the server initiates a restore job that recovers the data from secondary storage and stores it back on the NAS device. The intercepted call may now be served from the NAS. These operations occur automatically and without data agents for the NAS-based data.

Abstract: An improved information management system is described herein that can use artificial intelligence to classify data files (e.g., emails, documents, audio files, video files, etc.) and/or surface in a user interface the classification assigned to the data files. For example, a lightweight training or a heavyweight training can be employed to train classifiers to classify the data files. Use of artificial intelligence to classify data files may reduce the amount of computing resources that the information management system allocates to the data file review process because an auditor may be able to quickly identify those data files that meet the desired criteria using the classification and only request access to those data files. Thus, the information management system may be able to allocate more computing resources to normal or routine tasks, ensuring that such tasks are completed and/or completed in an appropriate amount of time.

Abstract: Improved techniques for disaster recover within storage area networks are disclosed. Embodiments include replicating a LIF of a primary cluster on a secondary cluster. LIF configuration information is extracted from the primary cluster. A peer node from a secondary cluster is located. One or more ports are located on the located peer node that match a connectivity of the LIF from the primary cluster. One or more ports are identified based upon one or more filtering criteria to generate a candidate port list. A port from the candidate port list is selected based at least upon a load of the port. Other embodiments are described and claimed.

Abstract: Systems, devices, methods, media, and instructions for automated image processing and content curation are described. In one embodiment a server computer system communicates at least a portion of a first content collection to a first client device, and receives a first selection communication in response, the first selection communication identifying a first piece of content of the first plurality of pieces of content. The server analyzes analyzing the first piece of content to identify a set of context values for the first piece of content, and accesses accessing a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content. In various embodiments, different content values, image processing operations, and content selection operations are used to curate the content collections.

Abstract: Machine learning techniques are disclosed that allow device contact list information to be leveraged in building better models that provide more accurate assessment of user transaction risks. A computing device may receive a contact list that includes a first set of user device identifiers and generates a contact graph for that user by associating the user device identifier with the first set as first-degree contacts. The computing device may then determine that a portion of the first set of the user device identifiers are stored in a contact database (e.g. on a server) and generate a user score based on user information associated with the first set, the contact graph, and a contact graph model. The computing device may provide the user score to a transaction assessment service as in input for the transaction assessment service deciding whether particular electronic transactions are approved for processing by an electronic service provider.

Abstract: A method performed by at least one computing system and including performing a document identifying operation on a corpus of documents. The documents are associated one each with a plurality of numeric tier scores. The operation identifies results including one or more of the documents. The method includes calculating each tier score in a portion of the numeric tier scores and organizing the documents into tiers based at least in part on the numeric tier scores. The portion of the numeric tier scores is identified based on the results. The tiers are ranked from most to least relevant and include relevant and non-relevant portions. The method includes sending any of the tiers in the relevant portion one at a time to one or more reviewer computing devices in an order determined by the ranking. Any of the tiers in the non-relevant portion are not sent to reviewer computing device(s).

Abstract: Methods, systems, and computer readable media related to generating a combined search query based on search parameters of a current search query of a user and search parameters of one or more previously submitted search quer(ies) of the user that are determined to be of the same line of inquiry as the current search query. Two or more search queries may be determined to share a line of inquiry when it is determined that they are within a threshold level of semantic similarity to one another. Once a shared line of inquiry has been identified and a combined search query generated, users may interact with the search parameters and/or the search results to update the search parameters of the combined search query.

Abstract: The disclosed computer-implemented method for write-once-read-many storage may include (1) receiving, at a file system on the computing device, a request to assign a write-once-read-many (WORM) attribute to a file, wherein the request is received from an application, (2) setting, in response to the request to assign the WORM attribute to the file, a WORM flag in an extended attribute associated with the file, and (3) associating with the file, in response to the setting of the WORM flag, a retention period attribute and read-only access until the end of the retention period. The provided systems and methods may provide per-file WORM support at a file system level using extended attributes of the file system. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Embodiments of the subject invention comprise a computer based system and methods to collect and compare the attributes of a group of entities using data representing topic data of the entity and interaction data between entities. Embodiments of the invention comprise using minimally invasive means to automatically collect and model both an entity's attributes such as their knowledge/work/interest as well as model the social interactions of the entity together with a means to identify opportunities to influence changes in the entity attributes. Minimally invasive means to collect and model attributes include semantic analysis and topic modeling techniques. Means to model social interactions include social network analysis techniques that can incorporate location data of the entity. Embodiments of the invention further provide a sharable index of the attributes of the entities and the group of entities.