International Business Machines Corporation

Amazon Technologies, Inc.

Zachary Paul Slayton

Anurag Srivastava

Michael J Bordash

Gilbert Barron

Louis F Roehrs

Therapon Skoteiniotis

Matthew S Canterbury

Tyler Gregg

Structured data templates and invocation statements may be used to dynamically define values, which allows for more efficient data encoding than traditional techniques. A given structured data template may be assigned a template identifier. A writer may generate an invocation statement that references a template identifier for a particular structured data template in order to generate a more compact representation of a structured portion of source data (based on the structured data template matching the structured portion of data). The structured data template may specify that any number of the fields is an 'unassigned' field. The invocation statement may specify values for these fields, resulting in a more compact representation of the structured portion of data. The use of an invocation statement and a structured data template eliminates the repetitive scaffolding of an object being written out.

Using structured data templates and invocation statements to dynamically define values for efficient data encoding

Portions of a multidimensional index for a database table may be selectively scanned for processing queries. A query may be received for a database table with a multidimensional index. A range of the multidimensional index may be identified for processing the query. Items mapped to different portions of the query may be scanned to apply the query. Some portions adjacent to a scanned portion may be skipped upon a determination that the adjacent portion does not include items that can satisfy the query. A result based on the scan operations can be provided in response to the query.

Selectively scanning portions of a multidimensional index for processing queries

Disclosed aspects include geo-fence management using a cluster analysis technique. A set of dynamic user data is received from a set of users. The cluster analysis technique may be used to process the set of dynamic user data. Accordingly, a geo-fence opportunity event is detected using the cluster analysis technique. Based on a selection criterion with respect to the geo-fence opportunity event, it is determined to provide an opportunity for a subset of the set of users. In response to making the determination, the opportunity can be provided for/to the subset of the set of users.

Geo-fence management using a cluster analysis technique

Disclosed aspects include geo-fence management using a cluster analysis technique. A set of dynamic user data is received from a set of users. The set of dynamic user data may have identification information which identifies one or more users, location information which indicates location for one or more users, and context information which indicates application context for one or more users. The cluster analysis technique may be used to process the set of dynamic user data. Accordingly, a geo-fence opportunity event is detected using the cluster analysis technique. Based on a selection criterion with respect to the geo-fence opportunity event, it is determined to provide an opportunity for a subset of the set of users. In response to making the determination, the opportunity can be provided for/to the subset of the set of users (e.g., sending a notification to the subset of the set of users).

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New York, NY, United States of America

Zachary Paul Slayton