Sap Se

Sap Ag

Ramshankar Venkatasubramanian

Dirk Wodtke

Ramprasad Rai

Hartmut K Vogler

Timo Hoyer

Suresh Babu

Heinz Kagermann

Hila Schlank

Heinz U Roggenkemper

Jie Zhao

Eckhard Farrenkopf

Christiane Kuntz-Mayr

Youneng Xiao

Daniela Karin Busse

Anand Tekkam

Shyam Ravindranathan

Kevin Wang

Brendan Bowles

Bipin Bihari Pandey

Shridhar Nayak

Riccardo Spina

Provided is a system and method for writing IoT data of an object in transit and business context associated with the IoT data and/or the object to a blockchain. In one example, the method may include receiving sensor data of an object that is in a multi-party transactional process, identifying dynamic context of the object based on a current position of the object within the multi-party transactional process, generating a data block comprising the received sensor data of the object and the identified dynamic context of the object, and storing the data block within a blockchain on an immutable distributed ledger.

Contextual IoT with blockchain

The disclosure generally describes methods, software, and systems, including a method for machine learning anomaly detection for a set of assets. Assets are analyzed using anomaly-detection analysis and a set of anomaly-detection rules. Each asset is associated with correlated records comprising characteristics of the particular asset and characteristic of non-asset-specific signals. Each anomaly-detection rule is associated with conditions determined to be indicative of a potential anomaly. At least a subset of the assets are provided for presentation in a user interface. Each asset is identified as being in a potential anomalous or non-anomalous state based on the anomaly-detection analysis. Input is received from a user identifying at least one asset as anomalous as a non-anomalous asset. Based on the received input, at least one anomaly-detection rule is modified that was applied to identify the asset as anomalous. The modified rule is stored for future analyses.

Machine learning anomaly detection

The disclosure generally describes methods, software, and systems, including a method for providing a suggested view of asset information for presentation. A set of correlated records is identified for a plurality of assets. The set of correlated records includes a correlated set of at least one characteristic of a particular asset and a characteristic of the non-asset-specific signals. The set of correlated records is analyzed to identify a set of anomaly-detection rules. In a presentation of at least a subset of the assets, an indication of assets associated with a potential anomaly identified. A suggested view is identified based on the potential anomaly and at least one characteristic/signal associated with the determination that the potential anomaly exists. The suggested view is provided for presentation in a user interface.

Suggestion of views based on correlation of data

A system includes determination of a first measure value associated with a first physical space and a first time period within the analytical data, dynamic determination of a time-dependent association between a first entity or event and the first physical, dynamic mapping of the first measure value to the first entity or event based on the time-dependent association, and presentation of the first measure value in association with the first entity or event.

Connected space

Embodiments of the present invention include architectures and methods for automated management of invoices. Embodiments of the present invention may include techniques for receiving and unifying invoice data, retrieving information about each invoice, verifying each invoice and resolving invoice exceptions. The present invention includes software components for efficiently processing invoices. In other embodiments, the present invention includes methods of processing an invoice.

System and method for management and verification of invoices

Systems and techniques for displaying detailed information in the context of a condensed enumeration of information. For example, in one aspect, in one aspect, a display includes a visual rendition of a table that systematically arranges condensed information in a collection of rows and columns for reference by a human user. The table includes information characterizing a collection of items. The visual rendition of the table comprises a region that renders additional detail regarding a first item in the collection. The region is disposed in the midst of the visual rendition of the table.

Displaying detailed information in the context of a condensed enumeration of information

Methods and apparatuses for interfacing an enterprise customer with a supplier are described herein. In one embodiment, in response to a request received from an enterprise customer via a first interface (e.g., a common or universal interface) of a Web service over the Internet for a service provided by a supplier, processing logic is configured to map the request from a first format compatible with the first interface to a second format compatible with a second interface coupling with a backend system of the supplier. Processing logic invokes a method of the backend system of the supplier via the second interface (e.g., supplier specific interface) to provide the requested service to the enterprise customer using information of the mapped request. The first interface is compatible with the requesting customer and the second interface is a specific interface to the backend system of the supplier. Functionality of mapping and the second interface are maintained by the supplier. Other methods and apparatuses are also described.

Interfaces between enterprise customers and suppliers

In one embodiment, the present invention includes methods for detecting fraudulent or erroneous invoices that use an associative memory and models of valid invoices. Incoming invoices may be applied against the models of valid invoices, and the models may access the associations of data elements in an associative memory and provide results to a decision engine. The decision engine may flag invoices that are nonconforming for further analysis. As more invoices and information about the invoices are gathered, the models and associative memory may be adapted to improve detection performance.

Growing community of inventors

Santa Clara, CA, United States of America

Ramshankar Venkatasubramanian