International Business Machines Corporation

Globalfoundries Inc.

Jeffrey James Jonas

Gregery Gene Adair

Robert J Butcher

Mudhakar Srivatsa

Dakshi Agrawal

Kirk J Krauss

Raghu Kiran Ganti

Frankie Elizabeth Patman Maguire

Charles Kinston Williams

Brian Eugene Macy

Shudong Huang

David Charles Martin

Brand Lee Hunt

Joshua L Herman

Paul D Hulseberg

Steven Bruce Dunham

Provided are techniques for testing pairings to determine whether they are publically known. It is determined whether a pairing from a record is publicly known by searching public data stores. The pairing is marked with an outcome of the determining. An operation is performed on the pairing based on the outcome.

Testing pairings to determine whether they are publically known

According to one embodiment of the present invention, a system for determining related entities includes at least one processor. The system identifies one or more candidate entities for a data object associated with an entity based on one or more features. The entity and candidate entities are each associated with one or more features and each feature is associated with one or more behaviors. The identified candidate entities related to the entity are determined based on the associated behaviors of the features of the identified candidate entities and the entity. Embodiments of the present invention further include a method and computer program product for determining related entities in substantially the same manner described above.

Context accumulation based on properties of entity features

Embodiments relate to reconciling different entity identifiers. A method of reconciling different entity identifiers of a same entity is provided. The method receives a plurality of series of location-time data items from a plurality of tracking systems that each track one or more entities. Each series of location-time data items is associated with an entity identifier. The method categorizes each location-data item into a space-time region. The method generates a track for each of the plurality of series of location-time data items based on the space-time regions into which the location-data items are categorized, and generates a track signature for each of the generated tracks based on a segment of the generated track. The method compares the track signatures to find matching track signatures. Based on a plurality of matching signatures, the method reconciles the plurality of entity identifiers associated with the plurality of matching signatures to a particular entity.

Track reconciliation from multiple data sources

A similarity between character strings is assessed by identifying first and second character strings as candidate similar character strings, determining a frequency of occurrence for at least one of the first and second character strings from a collection of character strings, and designating the first and second character strings as similar based on the determined frequency of occurrence.

String comparison results for character strings using frequency data

Techniques are disclosed for using spheres-of-influence to characterize network relationships, where a graph depicts stronger relationships as being closer to an entity than more tenuous relationships. That is, while an entity may have many first-degree relationships, some relationships are closer than others. Thus, relationships where one entity may have a greater degree of influence over another are characterized as being closer to an entity in a graph. Similarly, a tenuous first-degree relationship may be characterized as being at a greater 'depth' from the entity in the graph.

Using spheres-of-influence to characterize network relationships

Method, system, and computer program products, implementing and using techniques for processing data representing observations of entities. An anonymized key is generated. The anonymized key represents a spacetime region with which an entity is associated. The spacetime region represents a spatial region and a time interval. The entity is associated with the spacetime region based on spacetime coordinates for the entity.

Privacy enhanced spatial analytics

Provided are techniques for receiving a record, wherein the received record has a space-time feature, selecting candidate entities using the space time feature, performing space time analysis to determine whether the received record should be conjoined with a candidate entity from the candidate entities, and, in response to determining that the received record should be conjoined with the candidate entity, making an entity resolution assertion by conjoining the received record and the candidate entity to form a newly conjoined entity.

Space and time for entity resolution

Techniques are disclosed for performing identity resolution using life arcs as a feature. Space and time data may be received for an entity. A life arc template may be provided that specifies data that a life arc for each entity should include. A life arc may be generated for the entity based on the space and time data and the life arc template. An assertion for identity resolution may be made for the entity, based on the generated life arc.

Life arcs as an entity resolution feature

Provided are techniques for incrementally integrating and persisting context over an available observational space. At least one feature associated with a new observation is used to create at least one index key. The at least one index key is used to query one or more reverse lookup tables to locate at least one previously persisted candidate observation. The new observation is evaluated against the at least one previously persisted candidate observation to determine at least one relationship. In response to determining the at least one relationship, a threshold is used to make a new assertion about the at least one relationship. The new observation is used to review previous assertions to determine whether a previous assertion is to be reversed. In response to reversing the previous assertion, the new observation, the new assertion, and the reversed assertion are incrementally integrated into persistent context.

Incremental context accumulating systems with information co-location for high performance and real-time decisioning systems

A method and system for processing data into and in a database and for retrieving the processed data is disclosed. The data comprises identifiers of a plurality of entities. The method and system comprises: (a) processing data into and in a database, (b) enhancing received data prior to storage in a database, (c) determining and matching records based upon relationships between the records in the received data and existing data without any loss of data, (d) enabling alerts based upon user-defined alert rules and relationships, (e) automatically stopping additional matches and separating previously matched records when identifiers used to match records are later determined to be common across entities and not generally distinctive of an entity, (f) receiving data queries for retrieving the processed data stored in the database, (g) utilizing the same algorithm to process the queries and (h) transferring the processed data to another database that uses the same algorithm.

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Las Vegas, NV, United States of America

Jeffrey James Jonas