Method and an apparatus for clustering process models

• US 8,180,627 B2
• Filed: 07/02/2008
• Issued: 05/15/2012
• Est. Priority Date: 07/02/2008
• Status: Active Grant

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Goller, Mathias, Pomberger, Gustav, Weber, Norbert, Bögl, Andreas, Grömer, Alexandra
• Primary Examiner(s): Vo, Huyen X.
• Application Number:
  US12/166,647
• Publication Number:
  US 20100004923A1
• Time in Patent Office: 1,413 Days
• Field of Search: 704/243, 704/244, 704/245, 704/250, 704/257, 704 1- 10, 704/251, 704/270, 704/270.1, 1/1
• US Class Current: 704/9
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

The invention relates to an apparatus for clustering process models each consisting of model elements comprising a text phrase which describes in a natural language a process activity according to a process modeling language grammar and a natural language grammar, wherein said apparatus comprises a process object ontology memory for storing a process object ontology, a distance calculation unit for calculating a distance matrix employing said processing modeling language grammar and said natural language grammar, wherein said distance matrix consists of distances each indicating a dissimilarity of a pair of said process models, and a clustering unit which partitions said process models into a set of clusters based on said calculated distance matrix.

Claims

1. An apparatus for clustering process models each consisting of model elements comprising a text phrase which describes in a natural language a process activity according to a process modeling language grammar and a natural language grammar,

wherein said apparatus comprises:

(a) a process object ontology memory for storing a process object ontology;

(b) a distance calculation unit for calculating a distance matrix employing said processing modeling language grammar and said natural language grammar, wherein said distance matrix consists of distances each indicating a dissimilarity of a pair of said process models; and

(c) a clustering unit which partitions said process models into a set of clusters based on said calculated distance matrix.

2. The apparatus according to claim 1,

wherein the distances are calculated by said distance unit according to a selected calculation level, which is selectable between

a native calculation level,

a term calculation level,

an object calculation level,

an activity calculation level.

3. The apparatus according to claim 1,

wherein said clustering unit partitions said process models by means of a menoid-based clustering algorithm.

4. The apparatus according to claim 1,

wherein said process modeling language comprises UML (Unified Model Language)-model, an EPC (Event-driven Process Chain)-model, or a petri-network.

5. The apparatus according to claim 1,

wherein said model elements are labeled by text phrases each comprising at least one term.