Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolvedrequest by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency databa

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: A low-latency database analysis system using an object index may include obtaining data expressing a usage intent, and, in response to a determination that the data expressing the usage intent includes object search request data including a user identifier and zero or more object search terms, obtaining, from an object-index responsive to the object search request data, object indexing data for an object, obtaining object detail data for the object, obtaining an object visualization capture for the object, and outputting object search response data including the object visualization capture and at least a portion of the object detail data for presentation to a user.

Abstract: A low-latency database analysis system using an object index may include obtaining data expressing a usage intent, and, in response to a determination that the data expressing the usage intent includes object search request data including a user identifier and zero or more object search terms, obtaining, from an object-index responsive to the object search request data, object indexing data for an object, obtaining object detail data for the object, obtaining an object visualization capture for the object, and outputting object search response data including the object visualization capture and at least a portion of the object detail data for presentation to a user.

Abstract: A low-latency database analysis system outputs visualization data for presenting a visualization representing results data responsive to the request for data, and, in response to outputting the visualization data, generates a diverse plurality of candidate modifications for the request for data, outputs candidate modification data for presenting the diverse plurality of candidate modifications in association with the presentation of the visualization representing the results data, in response to outputting the candidate modification data, obtains user input data identifying a candidate modification from the diverse plurality of candidate modifications as a selected modification, in response to the user input data, executes a data-query expressing the request for data modified by the selected modification to obtain second results data responsive to the request for data modified by the selected modification, and in response to the second results data, outputs visualization data for presenting a visualization re

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: A low-latency database analysis system using an object index may include obtaining data expressing a usage intent, and, in response to a determination that the data expressing the usage intent includes object search request data including a user identifier and zero or more object search terms, obtaining, from an object-index responsive to the object search request data, object indexing data for an object, obtaining object detail data for the object, obtaining an object visualization capture for the object, and outputting object search response data including the object visualization capture and at least a portion of the object detail data for presentation to a user.

Abstract: A database server receives a request from a client application for performing a data transaction on persistent data storage. The request is sent to a set of replication servers. An acknowledgement for the request is received from each replication server, including a start sequence number and an end sequence number for data that is stored in local cache of the replication server, and a latest committed sequence number for data that was written to the persistent data storage by the replication server. A maximum value of latest committed sequence numbers received from the set of replication servers is determined. For each replication server, it is examined whether there is a gap between the start sequence number for data stored in local cache and the maximum value of the latest committed sequence numbers. Based on the examining, it is determined whether there is an occurrence of loss of data.

Abstract: A database server receives a request from a client application for performing a data transaction on persistent data storage. The request is sent to a set of replication servers. An acknowledgement for the request is received from each replication server, including a start sequence number and an end sequence number for data that is stored in local cache of the replication server, and a latest committed sequence number for data that was written to the persistent data storage by the replication server. A maximum value of latest committed sequence numbers received from the set of replication servers is determined. For each replication server, it is examined whether there is a gap between the start sequence number for data stored in local cache and the maximum value of the latest committed sequence numbers. Based on the examining, it is determined whether there is an occurrence of loss of data.

Abstract: A database server receives a request from a client application for performing a data transaction on persistent data storage. The request is sent to a set of replication servers. An acknowledgement for the request is received from each replication server, including a start sequence number and an end sequence number for data that is stored in local cache of the replication server, and a latest committed sequence number for data that was written to the persistent data storage by the replication server. A maximum value of latest committed sequence numbers received from the set of replication servers is determined. For each replication server, it is examined whether there is a gap between the start sequence number for data stored in local cache and the maximum value of the latest committed sequence numbers. Based on the examining, it is determined whether there is an occurrence of loss of data.

Abstract: A write request is received at a database server from a client application for writing data to persistent data storage. In response to receiving the write request, the database server selects a set of multiple replication servers. The data is sent from the database server to the selected set of multiple replication servers for writing to the persistent data storage. Confirmation is received at the database server from replication servers in the selected set of multiple replication servers. In response to receiving confirmation from the replication servers in the selected set of multiple replication servers, the database server sends to the client application information indicating success of the write request.

Abstract: A replication server receives a first write request from a database server for writing first data to persistent data storage. The replication server determines that the first write request is designated as asynchronous. In response to determining that the first write request is asynchronous, the first data is saved to local cache at the replication server and an acknowledgement is sent to the database server. The local cache stores second data to be written to persistent data storage when the first data is saved to the local cache. The first data and the second data are written from the local cache to the persistent data storage in a batch operation.

Abstract: A database server receives a request from a client application for performing a data transaction on persistent data storage. The request is sent to a set of replication servers. An acknowledgement for the request is received from each replication server, including a start sequence number and an end sequence number for data that is stored in local cache of the replication server, and a latest committed sequence number for data that was written to the persistent data storage by the replication server. A maximum value of latest committed sequence numbers received from the set of replication servers is determined. For each replication server, it is examined whether there is a gap between the start sequence number for data stored in local cache and the maximum value of the latest committed sequence numbers. Based on the examining, it is determined whether there is an occurrence of loss of data.

Abstract: One embodiment of the present invention provides a system that selectively deletes clusters of conceptually-related words from a probabilistic generative model for textual documents. During operation, the system receives a current model, which contains terminal nodes representing random variables for words and contains one or more cluster nodes representing clusters of conceptually related words. Nodes in the current model are coupled together by weighted links, so that if an incoming link from a node that has fired causes a cluster node to fire with a probability proportionate to a weight of the incoming link, an outgoing link from the cluster node to another node causes the other node to fire with a probability proportionate to the weight of the outgoing link. Next, the system processes a given cluster node in the current model for possible deletion. This involves determining a number of outgoing links from the given cluster node to terminal nodes or cluster nodes in the current model.

Abstract: Methods, computer program products, and systems related to providing gadgets that generate content based on entities extracted according to patterns defined by extractors are provided. A plurality of distinct extractors that define patterns for identifying entities in text are received from a plurality of users. The extractors are stored in a repository. The pattern defined by each of the extractors is processed into a pattern matching engine. The extractors are made available for subscription from a first user subscribing to a first extractor. A modification indication is received from a composition program regarding a first document of a first user, and in response to receiving the modification indication, the pattern matching engine corresponding to the first extractor is applied to the first document and identifies a first entity. The first entity is provided to a first software gadget that presents information relating to the first entity to the user.

Abstract: A system and method of voice communication with a machine are provided. The system includes a guide for containing at least one input element disposed in an arrangement, the arrangement having a coordinate system for locating the input element, and a processor for processing a user selection of the input element.