Emc IP Holding Company LLC

Emc Corporation

Rodrigo Dias Arruda Senra

Adriana Bechara Prado

Karin Breitman

Percy E Rivera Salas

Victor Bursztyn

Rômulo Teixeira De Abreu Pinho

Jonas Furtado Dias

Vinícius Michel Gottin

Angelo E M Ciarlini

André De Almeida Maximo

Diego Salomone Bruno

Rodrigo De Souza Lima Espinha

Caio Souza

Methods and apparatus are provided for evaluating combinatorial processes using simulation techniques and multiple parallel statistical analyses of real-world data. A simulation model is generated that simulates one or more steps of a combinatorial process. The simulation model comprises key features of the combinatorial process. A plurality of first data mining tasks are performed in parallel over real data of the combinatorial process to obtain key feature prediction models that estimate the key features. The key feature prediction models are bound to the simulation model. Query types to be supported are identified and a plurality of simulation runs are generated in parallel, comprising simulated data for the supported query types. A plurality of second data mining tasks are performed in parallel over the plurality of simulation runs to build global prediction models to answer queries of each supported query type. An answer to a user query is determined using the global prediction models.

Methods and apparatus for evaluation of combinatorial processes using simulation and multiple parallel statistical analyses of real data

Person-centric multi-channel opinion mining is performed in a single data repository, such as a data lake. An exemplary method comprises obtaining multi-channel heterogeneous data from a plurality of channels; identifying entities that are targets of opinion information across the plurality of channels; extracting a plurality of user identities from the plurality of channels; aligning the plurality of extracted user identities across the plurality of channels to link common user identities; identifying the entities that are targets of the opinion information of the extracted user identities; linking opinion information of the extracted user identities with a user identity associated with an opinion holder that expressed the opinion information; determining whether the opinion information comprises a positive or negative opinion; and providing a summary of the opinion information of a given opinion holder. Sentiment polarity classification algorithms optionally determine whether opinion information comprises a positive or negative opinion and assign a polarity score. An influencer score of the opinion holder is optionally assigned to the opinion information.

Methods and apparatus for person-centric multichannel opinion mining in data lakes

Methods and apparatus are provided for integrating a plurality of different database types in a semantic multi-database data lake. An exemplary method comprises providing a plurality of databases having different database types; translating ontology definition language database commands obtained from a user into a plurality of data definition language and/or data manipulation language commands supported by the different database types in order to replicate data from the user to each of the different database types; obtaining a query specified in a query language of a given database; and delegating the query to the given database. A plurality of cluster gateways optionally manage a corresponding plurality of clusters of database instances and wherein queries are delegated to a given database instance by delegating the queries to the appropriate cluster gateway. Dark data that was not queried by any supported query language in a predefined period of time can be detected.

Methods and apparatus for a semantic multi-database data lake

Methods and apparatus are provided for real-time ad hoc querying of data records, such as call detail records. An exemplary method comprises obtaining data records, wherein each data records comprises a plurality of fields and wherein one or more fields are used to aggregate a history of the data records; storing the data records in a consolidation queue (and optionally, a waiting queue), based on predefined indexing criteria; storing the data records from the consolidation queues in a historical database based on one or more predefined criteria related to a queue length and/or a time interval; creating a pre-processed index that maps indexed information for a given entity to a portion of the historical database; and, in response to a user query regarding attributes of the given entity: retrieving the data records related to the given entity from the historical database based on the pre-processed index for the given entity; storing the retrieved data records of the given entity into an in-memory database; and processing the retrieved data records of the given entity to answer the one or more user queries.

Real-time ad hoc querying of data records

Content planning techniques are provided that recommend content features based on the investment interest of advertisers in various audience segments and historical audience measurements. An exemplary method comprises obtaining historical data comprising content preferences indicating a performance metric for each pair of a plurality of content items and audience segment, wherein the content items comprise a plurality of content features indicating characteristics of a corresponding content item; obtaining, for each of a plurality of advertisers, a weight indicating a future interest of a given advertiser in a given audience segment; calculating a pairwise similarity between a vector of the content preferences and a vector of the weights for the plurality of the audience segments to obtain a ranked list of the content items sorted by the pairwise similarity; and generating a summarization of the content features to be used in future content items based on the ranked list.

Recommending features for content planning based on advertiser polling and historical audience measurements

Methods and apparatus are provided for integrating heterogeneous multi-channel data using ontologies. An exemplary method for integrating multi-channel heterogeneous data comprises obtaining a domain-specific mediator ontology; identifying a plurality of target channels; identifying entities pertinent to each of the plurality of channels; describing the entities pertinent to each of the plurality of channels using an ontology description language to generate a plurality of channel specific ontologies; aligning the channel specific ontologies with the domain-specific mediator ontology to generate aligned channel specific and domain-specific mediator ontologies; extracting a plurality of user identities from the plurality of channels; aligning the plurality of extracted user identities across the plurality of channels to link common user identities; generating at least one user profile for at least one of the aligned user identities; and correlating at least one user profile with the aligned channel specific and domain-specific mediator ontologies to generate an omni-channel ontology that integrates the multi-channel heterogeneous data.

Growing community of inventors

Rio de Janeiro, Brazil

Rodrigo Dias Arruda Senra