International Business Machines Corporation

Geetha Sravanthi Pulipaty

Abhishek Seth

Soma Shekar Naganna

Neeraj Ramkrishna Singh

James Albert O'Neill, Jr

Martin Oberhofer

Mohammad Khatibi

Scott Schumacher

Shettigar Parkala Srinivas

Chitra A Iyer

Prabhakaran Ramalingam

Mark Wang

Alexandre Luz Xavier Da Costa

Ruolin Wu

Rishabh Saraf

Mohit Singh Chouhan

An approach for accessing multi-attribute data records of a master data management system. The method comprises: enhancing the master data management system with one or more search engines for enabling data record access. A request of data may be received at the master data management system. A set of one or more of the multiple attributes, referenced in the received request, may be identified. A combination of one or more of the search engines of the master data management system, whose performances for searching values of at least part of the set of attributes fulfil a current selection rule may be selected. And, the request may be processed using the combination of search engines. At least part of the results of the processing may be provided, and the selection rule may be updated based on user operations on the provided results, the updated selection rule becoming the current selection rule.

Method for accessing data records of a master data management system

A method, a structure, and a computer system for mapping data fields. The exemplary embodiments may include, based on determining that a first data set and a second data set contain homogenous data, mapping at least one column of the first data set to at least one column of the second data set based on comparing at least one of relative column position and unique value sets. Based on determining that the first data set and the second data set contain heterogeneous data, the exemplary embodiments may include mapping the at least one column of the first data set to the at least one column of the second data set based on a difference between distribution signatures of unique value sets within each of the first data set and the second data set being less than a threshold.

Mapping of heterogeneous data as matching fields

A method for receiving an additional dataset including a plurality of additional data records; determining a record type using classifiers and an internal domain knowledge corpus; dividing the plurality of additional data records into a plurality of indexing groups; assigning the given additional data record to a match set based on completeness and similarity of natures of attributes of the given additional data record; and assigning the given additional data record to and a comparison group based on completeness and similarity of natures of attributes of the given additional data record.

Automatic generation of a matching algorithm in master data management

An approach for tuning a data management system is provided. A processor retrieves one or more samples pairs of record data. A processor determines an error rate regarding the performance of a matching operation of a data management system based on the one or more sample pairs. In response to the error rate being above a value, a processor adjusts at least one threshold value associated with the matching operation of the data management system.

Automatic tuning of thresholds and weights for pair analysis in a master data management system

A method is disclosed for a database system that includes a set of data blocks comprising records having attributes. The set of data blocks are instances of at least one block type. The block type is defined by a subset of one or more attributes of the attributes. An instance of the block type comprises records having one distinct group of values of the subset of attributes. The method includes detecting that a subset of one or more data blocks of the block type, of the set of data blocks, reached a first maximum number of records. The method includes determining an additional attribute of the attributes to define a new block type by the combination of the additional attribute and the subset of attributes that define the block type. The method includes creating one or more data blocks which are instances of the new block type.

Method for dynamic data blocking in a database system

Configuring a data management system by receiving user interaction data associated with search results associated with a first system configuration, identifying a usage pattern in the user interaction data using a first machine learning model, and altering the first system configuration according to the usage pattern.

Data management configuration tuning through link preference detection

A first score associated with matching between entity records of a plurality of entities of master data of an MDM system is received. A set of entity records with a first score above a lower threshold score and below an upper threshold score is identified as unresolved; neither confirmed as matched or unmatched. A second score associated with relationships between entity records is generated. Overall scores for pairs of the set of entity records are determined by combining the first matching score with the second relationship score. The overall score of respective pairs of the set of entities is compared to the upper threshold, and if the upper threshold is exceeded, then the information of the pair of entity records of the set of entity records are combined into a single record, and redundant entity records are removed from the MDM system.

Entity resolution of master data using qualified relationship score

The present disclosure relates to a method for a secure storage, matching and linking of data records. The method comprises: receiving a current data record having one or more attributes, each attribute having an attribute value. For each attribute of at least part of the attributes a predefined set of variations of the attribute value of the attribute may be generated. The received attribute values may be encrypted resulting in an encrypted record and the generated sets of variations may be encrypted. The encrypted record may be stores in a storage system in association with the respective encrypted sets of variations.

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Bengaluru, India

Geetha Sravanthi Pulipaty