Sap Se

Johannes Meinecke

Gregor Hackenbroich

Lars Dannecker

Katja Pfeifer

Dave Parsons

Paul Binks

Simon Moscrop

Jeremie Brunet

Richard Pilz

Jan Rittinger

Franz Josef Grueneberger

Tom Spiegler

Adrian Mocan

Jan Schole

Julian Harttung

Thomas Beck

Anja Jugel

Sead Pozderac

The present disclosure involves systems, software, and computer implemented methods for automatically extending a partially-editable dataset copy. One example method includes identifying, for a data set, extension filter criteria that extends a current filter that defines an editable portion of the data set. An extended filter is automatically generated for the data set based on the extension filter criteria and the current filter. Additional data is copied into the partially-editable copy of the data set based on the extended filter and the current filter to generate an updated partially-editable copy of the data set. The current filter is replaced with the extended filter to create a new current filter. An updated exposed view is generated using the new current filter that exposes the updated partially-editable copy of the data set and an updated non-editable portion of the data set.

Automatic extension of a partially-editable dataset copy

The present disclosure involves systems, software, and computer implemented methods for automatically generating a partially-editable dataset copy. One example method includes receiving an edit request from a user to edit a data set. A filter for the data set is determined, based on a context of the edit request. The filter is used to generate a partially-editable copy of the data set that includes the editable portion of the data set. An exposed view of the data set is generated that exposes the partially-editable copy of the data set and a non-editable portion of the data set. The exposed view of the data set is provided to the user and a change to a data item in the editable portion of the data set is received. The data item in the partially-editable copy of the data set is updated based on the change.

Efficient support for automatic generation of a partially-editable dataset copy

An aggregation service aggregates extraction results from diverse named entity recognition ('NER') services, which can help improve the quality of extracted information. In some cases, the aggregation service considers differences in entity type classifications when aggregating extraction results from different NER services. The aggregation service can also consider performance characteristics (e.g., error rates) for the different NER services. For example, the aggregation service receives extraction results generated for a document corpus according to an entity type schema for each of multiple different NER services, then aggregates the extraction results based at least in part on relations between entity types for the NER services. For a given annotation area, the computing system can identify hypotheses and rank the hypotheses according to an aggregation approach. For some types of aggregation approach, the computing system uses weight values, error path values and/or other performance characteristics determined during training for the NER services.

Aggregating results from named entity recognition services

Allocation within a database environment is performed by processing a sequence of steps, each of which is described by an allocation processing block. The allocation processing block receives three inputs (input tables or input view) and computes a result. Related apparatus, systems, techniques and articles are also described.

Flexibly performing allocations in databases

A reallocation processing block including a computing system including one or more data processors receives a base table, a reference table, and at least one assignment path table. Subsequently, rules from the at least one assignment path table are applied to the base table and the reference table by reallocating values between at least two existing data objects. A results table is generated with the reallocated values in the at least two existing data objects. A reallocated value is compared with a threshold value to determine the need for an iteration. At least one of the activities described is implemented using at least one data processor. Related apparatus, systems, techniques and articles are also described.

Flexibly performing reallocations in databases

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Dresden, Germany

Johannes Meinecke