Sap Se

Business Objects Software Limited

Kimberly Starks

Jeffrey Woody

Prasanthi Thatavarthy

Phil Tinari

Claudia Lehmann

Johan Raffin

Marius Obert

Srinivasan Kumar

Michael Alexander

Jeffery Woody

Xin Wen

Shibajee Dutta Gupta

In one embodiment, a complex query includes components that are arranged in a hierarchical structure including a first type of filter and a second type of filter and are connected by connectors. The method selects a first data set and selects a second data set for the components. The second data set being generated by processing data in the first data set for the second type of filter and the second data set includes entries describing a result of the processing. The first type of filter is applied to the first data set and the second type of filter to the second data set for the components where the information describing the result is used by the second type of filter to filter entries and first type of filter filters entries based on column values in the first data set. The method combines outputs of the components using the connectors.

Complex filter query of multiple data sets

A processing tool is described that can evaluate a plurality of fields in a plurality of records and assign a scoring measure to each field based on the evaluation of each field. The scoring measures can provide an indication as to the uniqueness in content within each field, which can assist with determining one or more fields that are most useful for performing a search to identify similar records.

Domain agnostic similarity detection

A method is provided for forming an entity cluster. In this method, a plurality of entities found in one or more data sources are identified. An entity may represent a word or a phrase found in the one or more data sources. The plurality of entities may then be organized into groups, where each group has a master entity and a set of subordinate entities. The groups are formed using a first comparison criteria. Then, using a second comparison criteria, a first group is associated with a second group. The second comparison criteria may compare the master entities associated with the first and second groups. Based on the association between the first group and the second group, the method can then determine that the first entity is related to the second entity.

Entity clustering via data services

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Fairfield, OH, United States of America

Kimberly Starks