Abstract: An approach is described for representing search results via a three-dimensional matrix. An associated method may include receiving a search query, querying at least one database based upon the search query, and receiving results to the search query from the at least one database. The method further may include representing the results via a three-dimensional matrix graphically depicting a plurality of categories corresponding to the results. Each of the plurality of categories may be associated with the results via a respective tag in the at least one database. Upon detecting activity from an input device, the method further may include filtering the plurality of categories of the three-dimensional matrix, and prioritizing the results based upon the filtering. Representing the results via the three-dimensional matrix may include presenting the results in a list correlated to the three-dimensional matrix, and prioritizing the results based upon the filtering may include prioritizing the list.

Abstract: An executable utility is injected into cloud-based virtual machines (VMs) that are subject to backups by a data storage management system tasked with protecting the cloud-based VMs and their associated data. The utility is injected into a target VM which is “live” and operating. The utility analyzes the VM's live volume to discover data extents therein, and for each extent computes a respective checksum and determines whether the extent is a “hole.” Afterwards, checksums help identify changed data in successive snapshots of the live volume, so that only changed data will be read and backed up in incremental backups. Time is saved in performing the backup operation first by pre-warming the backup's source volume in parallel with the utility analyzing the live volume, and second by skipping read operations for extents unchanged since a preceding backup. The resulting incremental backup operation is sped up as compared to prior art approaches.

Abstract: Humans have collaborated in both small and large groups for thousands of years, sometimes achieving great feats for the good of all mankind. However, most groups have failed to achieve greatness, often because of poor group “chemistry” and/or because of missing skills or insights. These problems typically arise because group organizers build groups using human mental processes that suffer from social, racial, gender, ethnic, or other unconscious biases. To reduce impact of these biases and help organizers form more effective groups or teams, the present inventors have devised, among other things, an exemplary system that subdivides a group of user data structures into subgroups, based on similarities between electronic surveys and/or other data types, such as social media and network analysis data types. The system further includes user interfaces for creating surveys, implementing user preferences regarding subgroup membership and sizes, controlling the subdivision process, and displaying the subgroups.

Abstract: An example of an apparatus including a network interface to receive first metadata and second metadata. The first metadata is associated with a first data source and the second metadata is associated with a second data source. The apparatus includes a processor to determine a first series of variance values associated with first metadata and second metadata, and to determine a second series of variance values associated with first metadata and second metadata. Furthermore, the apparatus includes a memory storage unit to store the first series of variance values and the second series of variance values. The apparatus includes an analysis engine to analyze the first series of variance values and the second series of variance values to confirm compatibility between the first data source and the second data source. The second series of variance values is to be analyzed after the first series of variance values is passed.

Abstract: In one embodiment, a computer-implemented method executable by a computer to process metadata of a data source is provided. The method includes: processing, by a processor of the computer, the metadata to determine a graph of nodes and edges; converting, by the processor of the computer, the graph from a cyclic graph to an acyclic graph; converting, by the processor of the computer, the acyclic graph to a listing; performing, by the processor of the computer, a topological sort on the listing; and generating a report that includes the sorted listing.

Abstract: Systems and methods for searching data are disclosed. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving a sample dataset and identifying a data schema of the sample dataset. The operations may include generating a sample data vector that includes statistical metrics of the sample dataset and information based on the data schema of the sample dataset. The operations may include searching a data index comprising a plurality of stored data vectors corresponding to a plurality of reference datasets. The stored data vectors may include statistical metrics of the reference datasets and information based on corresponding data schema. The operations may include generating, based on the search and the sample data vector, one or more similarity metrics of the sample dataset to individual ones of the reference datasets.

Abstract: A method for processing snapshots and a distributed block storage system, the method including: acquiring the number of read operations and the number of read/write operations for a data block in a distributed block storage system; on the basis of the number of read operations and the number of read/write operations, determining a target snapshot manner, wherein the target snapshot manner includes copying while writing or re-orienting while writing; on the basis of the target snapshot manner, performing a snapshot operation on the data block in the distributed block storage system.

Abstract: Cloud storage systems and methods provide event-based user state synchronization among the various cloud elements. A global user directory is maintained on a remote cloud storage system. The global user directory includes a plurality of global user definitions associated with a plurality of user accounts, where each of the user accounts has access to one of a remote file system (RFS) hosted by the remote cloud storage system and a local file system (LFS) hosted by a local cloud storage system. As global user definition are altered on the remote cloud storage system, user events are generated and communicated to the local cloud storage system, where they are applied to synchronize the local user definitions with the global user definitions. The invention facilitates centralized control of user definitions, near real-time event delivery to local cloud storage systems, and separation of authentication processes from customers' active directory services.

Abstract: A data recovery method and apparatus are provided. The method retrieving metadata according to a request for data recovery, where the metadata corresponds to a snapshot. A snapshot type of the snapshot is determined according to the metadata, and data recovery is performed according to the snapshot type, to generate recovered data. A false snapshot of the recovered data is generated, and metadata corresponding to the false snapshot is stored.

Abstract: Methods and systems are described for a media guidance application that tailors media content recommendations for downloadable content to the current interests of the users. For example, the media guidance application may determine the current interests of a user based on the media content recently consumed by the friends of the user, and automatically download that media content. In such cases, the media guidance application may monitor social networks of the user for indications of media content that may have been recently consumed by the friends of a user as such media content is likely to be of current interest to the user. In response to detecting media content that was recently consumed by the friend of the user, the media guidance application may automatically download the media content to a device of the user.

Abstract: Functionalities of new data types are enabled for data stored using native data types (“recognized data types”) supported by DBMSs. Values having a latent data type may be stored using a recognized data type of a DBMS. That is, a value stored in a database table may be recognized by a DBMS as having a recognized data type (e.g., character string) but the value may also include information that indicates the value conforms to a particular latent data type. DBMSs compile database statements. The database statement can contain multiple expressions that may specify a latent data type or that may have a recognized data type but that also imply latent data types. By determining that various expressions have latent data types, operations that rely on the expressions as having a latent data type may be validated in a query and executed accordingly.

Abstract: Techniques for leveraging frequent patterns identified in a captured workload are provided. In one approach, multiple frequent patterns detected in a captured workload may be ordered by frequency to determine, for example, which patterns should be targeted for optimization. In another approach, a model of a captured workload is created, where the model comprises nodes that represent templates (which in turn correspond to requests) and edges that represent transitions between templates. The model is used to create an artificial workload, such as a workload that is twice as large as the originally-captured workload. The model may also be edited before creating the artificial workload. In another approach, workload models are compared to identify errors, regressions, or security issues. In another approach, an artificial workload is created for an application that is not yet deployed and then executed to determine whether the artificial workload or the originally-captured workload executed faster.

Abstract: User portrait obtaining method, apparatus, and storage medium are provided. The method includes: obtaining M training samples according to a user behavior log. An initialized user parameter matrix Wm×k and an initialized tag parameter matrix Hk×n are modified according to the M training samples by using a data fitting model, to obtain a final user parameter matrix Wm×k and a final tag parameter matrix Hk×n. Further, a user portrait matrix Pm×n is obtained according to the final user parameter matrix Wm×k and the final tag parameter matrix Hk×n. In the present disclosure, a user and a tag are parameterized, and a user parameter matrix and a tag parameter matrix are modified by using the data fitting model, so as to fit a training sample.

Abstract: One embodiment of the invention is directed to a method for performing efficient key range searches in a distributed computing system. The method may comprise, receiving a first key (e.g., an alphanumeric identifier). A key range tree map associated with the first key may be identified from a plurality of key range tree maps. In some embodiments, individual key range tree maps map a set of minimum range values to a set of index values. The method may further comprise determining an index value associated with a second key using the determined key range tree map. Transaction processing data associated with the first key may be determined using the index value and provided to the requesting source. Utilizing the plurality of key range tree maps as described herein enables a key range search to be performed using on-board memory of an electronic device.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a QMS executed within a first data center, a query definition provided from a browser of an analytics platform executed within the second data center, the query definition being stored in a query repository, being validated by the QMS based on analytical metadata, and being stored in a mirror query repository of the first data center, providing, after validation of the query definition, a calculation scenario as an object model based on the query definition, executing, by a calculation engine within the first data center, the calculation scenario to provide an analytical artifact including a query-level calculation view on transactional data stored in the first data center, and transmitting, by the first data center, the analytical artifact to the second data center to perform analytics on at least a portion of the transactional data stored in the first data center.

Abstract: Methods, systems and computer program products implementing hierarchical classification techniques are disclosed. A hierarchical classification system receives training data including labeled transaction records. The system determines tag sequences from the training data. The system clusters the tag sequences into clusters. The system determines a cluster-level classifier that is trained to predict a cluster for an input transaction record. The system determines a respective cluster-specific classifier for each cluster. The system trains the cluster-specific classifier to predict a label of entity of interest for an input transaction record, given a particular cluster. Upon receiving a test transaction record, the system first applies the cluster-level classifier to determine a particular cluster for the test transaction record, and then determines a label of entity of interest of the test transaction record by applying a cluster-specific classifier of that particular cluster.

Abstract: An apparatus as an aspect of the present invention is a factor analysis apparatus that analyzes a relationship between a target event that is a target of factor analysis and an assumed factor of the target event, and includes a similarity calculator, a first influence calculator, and a second influence calculator. The similarity calculator calculates a degree of similarity between a data item included in provided time-series data and the assumed factor. The first influence calculator calculates a first degree of influence indicating a degree of influence of the data item on the target event on the basis of time-series data of the data item and time-series data of the target event. The second influence calculator calculates a second degree of influence indicating a degree of influence of the assumed factor on the target event on the basis of the degree of similarity and the first degree of influence.

Abstract: A spatial-temporal storage method, system, and non-transitory computer readable medium, include, in a first layer, a geometric translation circuit configured to split spatial-temporal information into row keys and translate a geometry query into a range scan, and a multi-scan optimization circuit configured to compute an optimal read strategy to optimize the range scan translated by the geometric translation circuit into a series of block starting offsets and block sizes, and, in a second layer, a block grouping circuit configured to allow grouping of blocks in the second layer while preserving spatial data locality when splits of spatial-temporal information occur in the first layer.

Abstract: A method, system and computer program product are disclosed for searching for data. In one embodiment, the invention provides a method comprising identifying a query and a search scope including a set of specified entities; and for each of these entities, estimating a number of documents that would be identified in a search through the entity to answer the query. On the basis of this estimating, a subset of the entities is formed. The query and this subset of entities are sent to a search engine to search the subset of entities to answer the query. In one embodiment, the estimating includes collecting statistical information from queries to build up a historical cache using heuristics or machine learning techniques, wherein the query includes a key word and a scope, and the historical cache contains a maximum number of returned results for an entity given the queries executed.

Abstract: Methods and systems for processing incoming data in real-time are described herein. The incoming data is processed in real-time to generate data records that may be improved over time, for example, by automatically correcting inaccurate data in the records. In some embodiments, when data is received, a real-time process is initially performed on the received data under a first time constraint to produce first data for a data record. Subsequently, one or more non-real-time processes are then performed on the received data under a second time constraint to produce second data for the data record. The second data may be used to update the data record, for example, to correct any inaccuracy caused by the real-time process of the received data. Preferably, the second time constraint is longer than the first time constraint.