Abstract: Concept expansion using tables, such as web tables, can return entities belonging to a concept based on an input of the concept and at least one seed entity that belongs to the concept. A concept expansion frontend can receive the concept and seed entity and provide them to a concept expansion framework. The concept expansion framework can expand the coverage of entities for concepts, including tail concepts, using tables by leveraging rich content signals corresponding to concept names. Such content signals can include content matching the concept that appear in captions, early headings, page titles, surrounding text, anchor text, and queries for which the page has been clicked. The concept expansion framework can use the structured entities in tables to infer exclusive tables. Such inference differs from previous label propagation methods and involves modeling a table-entity relationship. The table-entity relationship reduces semantic drift without using a reference ontology.

Abstract: System and methods are described to create successive abstractions of real and virtual environments and objects. A common framework is provided to define abstractions for a large collection of various input data feeds. It is assumed that environments are either instrumented to produce such messages or that they may contain sensors or smart devices that generate such messages. Incoming messages are analyzed preserving latency requirements and without imposing unduly heavy procedures. The analysis yields various abstractions at several scales that can be utilized by application programs. A system architecture using specialized storage mechanisms is proposed that preserves the latency requirements of the incoming data messages and the generated abstractions.

Abstract: Computerized systems for providing a personalized computing experience are provided through enriched calendar event data. The enriched calendar event data provides an event type, additional location data for the calendar event, and the likely user attendance. To determine the enriched calendar event data, a user location pattern, and a calendar event pattern are determined. As future calendar events are detected, a set of features for the future calendar events is determined. Past calendar events having features similar to the detected future calendar event can then be determined. A user location for the similar past calendar events can be determined to form a user behavior pattern model indicating a user location for the similar past calendar events. A predicted user location for the future calendar event can be determined based upon the similar past calendar events and the user behavior pattern model.

Abstract: A method, system and computer program product for performing video analytics on content, by collecting content (video data) from a plurality of sources, wherein the content pursues a streaming protocol; and performing at least one of storing the content in a local repository for downtime recording wherein on negative determination of a network connection, wherein servers directly coupled to a plurality of sources cache content until the network connection retains normalcy or performing analytics at least one of a real-time insight or an interactive insight or a batch insights on the content, and displaying to the user a resulting insight wherein the resulting insights are in a human readable form.

Abstract: A computer program product provides efficient multiple aggregation distinct processing. The computer program product including a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a processor to cause the processor to convert a query with multiple aggregation distincts into a two-stage group-by process using a nest operator. The two-stage group-by process including further program instructions to cause the processor to: perform a first stage group-by process including the nest operator taking a single input row, and concatenating a grouping key with a measure value for each aggregation distinct that forms multiple inputs to a single group-by table, and perform a second stage group-by process including the nest operator bringing together entries for each original group.

Abstract: A distributed database processing system for a database composed of data records organized into tables which processes unique index atoms consistently and concurrently. Each attempt to insert a new key value into such a unique index atom in any given node is routed to a unique index atom chairman for processing. The chairman determines whether the request will be granted. If the request is not granted, the requesting unique index atom continues to try to submit the insert. If the request is granted, the requesting unique index atom modifies the content thereof and broadcasts a replicated given unique index atom all other nodes that contain the replicated unique index atom.

Abstract: Increasing the efficiency of performing queries on databases by eliminating partitions during a database query. The database query configured to access a database table having one or more columns and one or more rows, the database query including a condition on a specified basis column. The database table being partitioned on the basis of the specified column, the specified column having one or more distinct values and the partitioning including mapping, by the at least one programmable processor, individual ones of the one or more distinct values to individual partitions causing each row in the table to be mapped to a specific partition. Candidate partitions and guaranteed partitions can be identified. The database query can be applied only to candidate partitions. All rows which satisfy the database query and all the rows of the guaranteed partition can be forward for processing.

Abstract: Application behavior is analyzed to determine relationships between data. Database objects accessed by an application are identified. Then, one or more relationships between the identified database objects are determined based on one or more from a group comprising statements of the application referring to the identified database objects and sets of the identified database objects accessed by different modules of the application.

Abstract: The present invention seeks to offer a system and method for recognizing patterns in key value identifier strings and seeks to provide a method for generating new unique key value identifier strings which follow pre-established patterns allowing users to keep a uniform format and simplify the future generation of key value identifiers.

Abstract: A computer-implemented method for copying data records from a first table residing in a database to a second table involves selecting a column of the first table as a parallelization column, identifying a number of distinct data record field values in the parallelization column of the first table and identifying a corresponding number of copy groups of data records. Each copy group of the data records includes the data records of the first table, which have the same distinct data record field value in the parallelization column of the first table. The method further involves setting up a corresponding number of copy processes; each copy process is configured to copy a respective copy group of data records from the first table to the second table.

Abstract: Some embodiments are directed to a method for determining, for a set of co-ordinate records associating co-ordinates with incident values, the numbers of incidents associated with co-ordinates within a query area. Co-ordinate data is stored as data representing a binary tree comprising leaf nodes, a root node and branch nodes wherein the leaf nodes are associated with individual items of co-ordinate data identified by the set of co-ordinate records, and the root node and branch nodes are each associated with a pair of child nodes, and are each associated with split values. In response to a query identifying a query area the binary tree is then recursively processed starting with the root node.

Abstract: Various technologies described herein pertain to automation of crowd-sourced polling. At least one query can be received. The at least one query includes a request. A poll can be automatically generated based upon the at least one query, where the poll corresponds to the request. The poll can be submitted to a crowdsourcing backend, where instances of the poll are administered on the crowdsourcing backend. Moreover, crowd-sourced responses to the instances of the poll can be retrieved from the crowdsourcing backend. The crowd-sourced responses to the instances of the poll can respectively include crowd-sourced responses to the request. The crowd-sourced responses to the request can be converted to a random variable. An operation can be performed upon the random variable. The operation can include one or more of a statistical analysis (e.g., hypothesis testing), bias correction, an arithmetic operation, expected value computation, standard deviation computation, etc.

Abstract: Relevant messages, or “hero results”, which are not ranked at the uppermost part of a time-based listing of search results are identified and such hero results can be displayed apart from the time-based listing of search results. A user can be provided with messages in a time-based presentation as well as messages in a relevance-based presentation. The user can be presented with the most relevant messages from a set of message generated from a search query, even where the most relevant messages are not the most recent ones.

Abstract: Implementations include actions of obtaining a set of entities based on one or more terms of a query, obtaining one or more entities associated with each live event of a plurality of live events, identifying a live event that is responsive to the query based on comparing at least one entity in the set of entities to one or more entities associated with each live event of a plurality of live events, determining that an event search result corresponding to the live event is to be displayed in search results, and in response: providing the event search result for display, the event search result including information associated with the live event, the information including an indicator of an occurrence of the live event.

Abstract: Disclosed in some examples are methods, systems, devices, and machine readable mediums for calculating an entity potential score for an entity that meets a defined entity selection criteria. The entity potential score quantifies an estimated likelihood that the entity will be successful in a predetermined timeframe by meeting predefined entity success criteria. Information on the entity may be determined (e.g., employee information, industry, financial information), various component subscores may be calculated and an entity potential score may be calculated for the entity. This entity potential score may be presented to one or more members of the network accessible computer-based service. For example, the entity potential score may be displayed along with a web-page describing the entity. The entity potential score may be searchable such that a user may specify a maximum, minimum, or range of entity potential scores as a search criteria for a search for entities.

Abstract: A disclosed computer-implemented method for tokenizing user-annotated names may include (1) identifying an example set of user-annotated names, (2) creating a custom dictionary that includes known keywords by (a) extracting a set of known keywords from the example set of user-annotated names and (b) assigning a frequency score to each known keyword in the set of known keywords based on the respective frequency of each known keyword within the example set, and (3) enabling the computing device to tokenize an additional user-annotated name of arbitrary structure by performing a semantic analysis including (a) assigning, using the custom dictionary, a frequency score to a substring of the additional user-annotated name based on the substring matching the known keyword and (b) splitting the additional user-annotated name into tokens according to a permutation of substrings that received a top combined frequency score. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for dynamic partition selection. One of the methods includes receiving a representation of a query plan generated for a query, wherein the query plan includes a dynamic scan operator that represents a first computing node obtaining tuples of one or more partitions of a table from storage and transferring the tuples to a second computing node that executes a parent operator of the dynamic scan operator. A partition selector operator is generated corresponding to the dynamic scan operator. A location in the query plan is determined for the partition selector operator. A modified query plan is generated having the partition selector operator at the determined location.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for dynamic partition selection. One of the methods includes receiving a representation of a query plan generated for a query, wherein the query plan includes a dynamic scan operator that represents a first computing node obtaining tuples of one or more partitions of a table from storage and transferring the tuples to a second computing node that executes a parent operator of the dynamic scan operator. A partition selector operator is generated corresponding to the dynamic scan operator. A location in the query plan is determined for the partition selector operator. A modified query plan is generated having the partition selector operator at the determined location.

Abstract: Systems, methods, and other embodiments associated with identifying non-technical line loss using data from smart meters in an electric grid are described. In one embodiment, a method includes querying a utility database to collect meter data, wherein the meter data is from electric meters connected to a transformer in an electric grid. Querying the utility database includes collecting the data according to a plurality of intervals over a period of time. Electric consumption and voltage variances are analyzed for the set of meters to identify a first set of intervals that satisfy a threshold for electric consumption and to identify a second set of intervals that satisfy a threshold for voltage variances. The first set of intervals is compared with the second set of intervals to determine whether the set of meters are associated with non-technical line loss.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.