Sap Se

Intelligent Views Gmbh

Sap Ag

Archim Heimann

Stefan Scheidl

Nico Licht

Klaus Reichenberger

Steffen Moldaner

Stephan Brand

Robert Heidasch

Michael Neumann

Christoph Meinel

Matthias Kaiser

Thomas Pohl

Klaus Herter

Otfried Von Geisau

Dieter Krisch

Christian Fuhlbruegge

Volker Faisst

Steffen Springborn

Silke Massmann

Andre Doerfler

Arno Mielke

Karlheinz Agsteiner

Alexander Stefan Adam

Thomas Kretz

Ulrich Spinola

Werner Sottong

Dorothea Martin

Katharina Sorge

A method and apparatus for determining relationships between objects in a meta-model semantic network is described. A contextual network graph comprising nodes and edges representing semantic objects and semantic relationships is generated from a meta-model of business objects from the meta-model semantic network. The contextual network graph is used to generate a unique identifier for each node and associated edge. The unique identifiers are used to compute information of cost and energy between the nodes. The information is stored in a meta-model semantic network database.

Distance in contextual network graph

In an embodiment, a method is provided for searching similar documents. Here, a document is accessed and terms from a metamodel semantic network is identified. The document is analyzed to identify a number of the terms from the metamodel semantic network that are also found in the document, and to identify a frequency of occurrence in the document for each term. A search is conducted for other documents having frequencies of occurrences that are similar to the identified frequency of occurrence. These other documents have been previously analyzed using the same terms from the metamodel semantic network.

Searches for similar documents

In an embodiment, a method is provided for utilizing a meta-model semantic network. In this method, a meta-model of the enterprise data is obtained. The meta-model provides semantic information regarding a definition of a business object. The meta-model is then used to generate a rule definition that maps enterprise data to a semantic object definition and a semantic relation definition. With the rule definition, embodiments may then generate a semantic object and a semantic relation from data extracted from the enterprise data. The semantic object and semantic relation are stored in the meta-model semantic network.

Semantic related objects

A semantic phrase suggestion engine that provides term and sentence suggestions based on context-specific user groups. Knowledge domains within a semantic network may be automatically derived from user software applications, and each term within the knowledge domain includes meta-data about the terms, e.g., term type and an importance indicator. The indicators may be defined within the context of specific user groups and relate to how many times that group has used the term (e.g., in documents, emails, etc.) The semantic phrase suggestion engine may also include spelling conditions and grammar conditions, which can then provide phrase suggestions according to the conditions and importance indicators, specific to a user group.

Semantic phrase suggestion engine

In example embodiments, a technique is provided to determine the similarity between two terms. For example, example embodiments may store a meta-model semantic network that includes a first and second term. Further, both the first and second terms are respectively associated with model and meta-model information. A request to calculate a term similarity value is received. A term similarity value expresses a correlation between the first term and the second term. The term similarity value is then calculated based on a comparison of the model and the meta-model information associated with the first and second terms.

Calculating term similarity using a meta-model semantic network

In an embodiment, a method is provided for conducting a search. In this method, a message is received from a client application. A user that initiated the message is identified and context information associated with the user is retrieved. Thereafter, a business object associated with the context information is identified and a domain associated with the business object is identified. Here, the domain includes a number of terms, and one or more of these terms are selected to be included in a query. A search of a data source can then be conducted using this query.

Data search using context information

A method, machine readable storage medium, and system for providing a self learning semantic search engine. A semantic network may be set up with initial configuration. A search engine coupled to the semantic network may build indexes and semantic indexes. A user request for business data may be received. The search engine may be accessed via a semantic dispatcher. And based on the access, search engine may update the indexes and semantic indexes.

Self-learning semantic search engine

A method, machine readable storage medium, and system for providing personalized semantic controls for semantic systems. A semantic network may be set up with initial configuration. A business application user interface, including semantic controls, may be coupled to the semantic network to interact with the semantic network. Semantic objects and relations may be defined in the semantic network for business terminology. A user request for business data may be received. The semantic network may update the objects and relations for business terminology based on the request. The business application user interface may provide for personalized semantic controls based on the updated objects and relations.

Personalized controls for a semantic system utilizing a central and a local semantic network

A cascading learning system for semantic search is described including the generation, training and testing of a domain-specific module for a domain-specific search. One or more input elements and output elements are specified for the domain-specific module with reference to a domain that relates these elements together through data sets that include related metadata. The related metadata may include semantic terms that are incorporated into a contextual network applicable to the domain.

Pluggable modules in a cascading learning system

Generation of an engineering change case is initiated by associating an identified problem for a product with an engineering change case template. The engineering change case can include a plurality of structured folders that can be populated with content characterizing the identified problem as well as proposed solutions to the identified problem with each folder being assignable to one or more users and having associated deliverables for such users. The various users populate the folders with content associated with the deliverables with at least a portion of the deliverables being delegable and requiring completion in a sequential order. Thereafter, generation of the engineering case can be finalized when an indication is received that all deliverables requiring approval have been completed. Otherwise, the engineering change case can be canceled. Related apparatus, systems, techniques and articles are also described.

Collaborative environment to assess, design, and implement product changes

Growing community of inventors

Wiesloch, Germany

Archim Heimann