Abstract: The present disclosure comprises systems and methods to mine association rules from a dataset provided in the input. This comprises methodologies for optimizing the dataset for efficient computation of association rules, other than methodologies for handling partially true data. Moreover, it includes methodologies for evaluating the mining process automatically and removing uninteresting rules. In addition, it includes methodologies for integrating experts in the evaluation of the rules. Finally, methodologies to automatically detect outliers, correct outliers, update truth values and complete missing data in the original dataset. The overall methodology is completely automated and provides numerous tuning parameters to fit most of the use cases, including a default value for each of the tuning parameters to simplify its usage.

Abstract: Methods and systems for enriching an information system containing information about companies with additional competitor information. The information system, which could be a database, a knowledge base, or a knowledge graph, is assumed to contain information about a plurality of single companies, the information comprising data such as industry codes, competitors, and possibly also keywords for each company. The disclosed methods determine new competitor pairs by combining (i) the generation of new competitor candidate pairs by inference from existing competitors and other company-specific knowledge with (ii) the validation of such competitor candidates pairs by checking for joint occurrence in documents of a document repository.

Abstract: The present disclosure comprises systems and methods to convert Existential Datalog source code into Differential Dataflow source code, whereby databases or knowledge graphs, some of whose relations are defined from other relations using Existential Datalog rules can be maintained incrementally.