Siemens Aktiengesellschaft

Xueyan Jiang

Volker Tresp

Maximilian Nickel

Yi Huang

A method is provided for calculating a relation indicator for a relation between entities based on an optimization procedure. The method combines the strong relational learning ability and the good scalability of the RESCAL model with the linear regression model, which may deal with observed patterns to model known relations. The method may be used to determine relations between objects, for instance entries in a database, such as a shopping platform, medical treatments, production processes, or in the context of the Internet of Things, in a fast and precise manner.

Calculating a relation indicator for a relation between entities

Systems and methods are provided for deriving a prediction from existing data by utilizing information extraction and machine learning, wherein both approaches can be optimized independently from each other. Optionally, deductive reasoning may also be combined with information extraction and machine learning and may as well be optimized independently from the other two functionalities. The two or three functionalities may utilize at least one set of data and may (at least partially) process various sets of data. The combined approach may produce significantly improved results, and may be implemented in various technical fields, applications and use cases involving, e.g., data mining or processing of huge amounts of data. The disclosed systems and methods may be applicable for all kinds of technical systems, e.g., medical, genetic research, or industry and automation systems.

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Munich, Germany

Xueyan Jiang