Lecture reference architecture_for_semantic_cms_part_i

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Lecture reference architecture_for_semantic_cms_part_i

  1. 1. Designing Semantic CMS – Part ISemantic CMS Community Lecturer Organization Date of presentation Co-funded by the 1 Copyright IKS Consortium European Union
  2. 2. Page: Part I: Foundations(1) Introduction of Content Foundations of Semantic (2) Management Web Technologies Part II: Semantic Content Part III: Methodologies Management Knowledge Interaction Requirements Engineering(3) (7) and Presentation for Semantic CMS(4) Knowledge Representation and Reasoning (8) Designing Semantic CMS Semantifying(5) Semantic Lifting (9) your CMS Storing and Accessing Designing Interactive(6) Semantic Data (10) Ubiquitous IS www.iks-project.eu
  3. 3. Page: 3 What is this Lecture about? We have seen ... Part III: Methodologies  ... how requirements for semantic content management Requirements Engineering (7) are defined in a systematic way. for Semantic CMS  ... a list of industry needs. Designing (8) Semantic CMS What is missing? Semantifying  An efficient way to design an (9) your CMS architecture for a semantic CMS that meets the defined (10) Designing Interactive requirements Ubiquitous IS www.iks-project.eu Copyright IKS Consortium
  4. 4. Page: 4 How to design a semantic CMS? What does the Conceptual Part 1 architecture of a Reference IKS Referencesemantic CMS look Architecture Architecture like? TechnicalHow can a semantic Part 2 Architectural CMS be realized? REST Architecture Style www.iks-project.eu Copyright IKS Consortium
  5. 5. Page: 5www.iks-project.eu Copyright IKS Consortium
  6. 6. Page: 6 Towards Semantic Content Management Content SemanticManagement Content Management extract knowledge from content Content Content Knowledge www.iks-project.eu Copyright IKS Consortium
  7. 7. Page: 7 How to build a Semantic CMS? Requirements from industry  Easy integration with existing CMS  Reuse features of existing CMS  Use RESTful interfaces  Semantic features as optional components Functional requirements  Automatic extraction of entities from text  Automatic extraction of relations between entities  Automatic categorization of content  Automatic linking of content  ... www.iks-project.eu Copyright IKS Consortium
  8. 8. Page: 8 What are semantic CMS?A Semantic CMS is a CMS with the capability ofinteracting with Presentation and Interaction Layersemantic metadata,extracting Semantic Lifting Layersemantic metadata,managing Knowledge Representation andsemantic metadata, Reasoning Layerand storing Persistence Layersemantic metadataabout content. www.iks-project.eu Copyright IKS Consortium
  9. 9. Page: 9 Traditional CMS Architecture for Content User Interface Presentation Layer Content Access Business Logic Layer Content ManagementAdministration Content Data Representation Content Data Model Layer Content Repository Persistence Layer www.iks-project.eu Copyright IKS Consortium
  10. 10. Page: 10Reference Architecture forSemantic CMSSemantic User Interaction Presentation & Interaction Layer Knowledge Access Knowledge Extraction Pipelines Semantic Lifting Layer Administration Knowledge Reasoning Knowledge Representation and Knowledge Models Reasoning LayerKnowledge Repository Persistence Layer www.iks-project.eu Copyright IKS Consortium
  11. 11. Page: 11 Semantic User Interaction Dealing with knowledge in semantic CMS raises the need an additional user interface level that allows the interaction with content, Example:  “A user writes an article and the SCMS recognizes the brand of a car in that article. An SCMS includes a reference to an object representing that car manufacturer – not only the brand name. The user can Semantic User Interaction Knowledge Access interact with the car manufacturer object and Knowledge Extraction Pipelines Administration see, e.g. the location of its headquarter. Knowledge Reasoning Knowledge Models Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  12. 12. Page: 12 Knowledge Access Access to inferred and extracted knowledge is encapsulated through a Knowledge Access layer It provides the access to knowledge for Semantic User Interaction. Semantic User Interaction Knowledge Access Knowledge Extraction Pipelines Administration Knowledge Reasoning Knowledge Models Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  13. 13. Page: 13 Knowledge Extraction Pipelines The main challenge for semantic CMS is the ability to extract knowledge in terms of semantic metadata from the stored content. A separate layer for Knowledge Extraction Pipelines encapsulates algorithms for semantic metadata extraction. Typically, knowledge extraction is a Semantic User Interaction multistage process [FL04] by applying Knowledge Access Knowledge Extraction Pipelines different IE/IR algorithms Administration Knowledge Reasoning Knowledge Models Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  14. 14. Page: 14 Pipeline Processing - Example Content Pre- Entity Relation Extraction Processing Extraction ExtractionJohn Miller has brought a Jaguar car this year. Person Car Time Manufacturer Relation www.iks-project.eu Copyright IKS Consortium
  15. 15. Page: 15 Reasoning After lifting content to a semantic level this extracted information may be used as inputs for reasoning techniques in the Reasoning layer Logical reasoning is a well-known artificial intelligence technique that uses semantic relations to retrieve knowledge about the content that was not explicitly known before. Semantic User Interaction Knowledge Access Knowledge Extraction Pipelines Administration Knowledge Reasoning Knowledge Models Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  16. 16. Page: 16 Knowledge Models Knowledge (representation) Models that define the semantic metadata are used to express knowledge Ontologies can be used to define semantic metadata that specifies so-called concepts and their semantic relations. Semantic User Interaction Knowledge Access Knowledge Extraction Pipelines Administration Knowledge Reasoning Knowledge Models Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  17. 17. Page: 17 Knowledge Repository Knowledge is stored in a Knowledge Repository that defines the fundamental data structure for knowledge State-of-the-art knowledge repositories implement a triple store where a triple is formed by a subject, a predicate, and an object A triple can be used to express any relation between a subject and an object Semantic User Interaction Knowledge Access Knowledge Extraction Pipelines Administration Knowledge Reasoning Knowledge Models Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  18. 18. Page: 18 Knowledge Administration Knowledge Administration includes the management of:  Semantic User Interaction templates,  Knowledge Extraction Pipeline management  Reasoning management to the administration of Knowledge Models and Repositories. Semantic User Interaction Knowledge Access Knowledge Extraction Pipelines Administration Knowledge Reasoning Knowledge Models Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  19. 19. Page: 19 Integration Semantic User Interface User Interface Semantic User Interaction Content Access Knowledge Access Knowledge Extraction Pipelines Content AdministrationAdministration Knowledge Management Content Reasoning Content Data Model Knowledge Models Content Repository Knowledge Repository www.iks-project.eu Copyright IKS Consortium
  20. 20. Page: 20 Implementation of the Reference Architecture Reference implementation within the IKS project  IKS: An open source community to bring semantic technologies to CMS platforms  New incubating project at the Apache Software Foundation http://incubator.apache.org/stanbol www.iks-project.eu Copyright IKS Consortium
  21. 21. Page: 21 Implementation of the Reference Architecture One year student project Information-Driven Software Engineering  Extract knowledge from unstructured software specification documents  Case study: 10.000 pages specification of German Health Card system www.iks-project.eu Copyright IKS Consortium
  22. 22. Page: 22 Breathing life to the Reference Architecture Semantic User Interface User Interface Semantic User Interaction Content Access Knowledge Access Knowledge Extraction Pipelines Content AdministrationAdministration Knowledge Management Content Reasoning Content Data Model Knowledge Models Content Repository Knowledge Repository Content Management ID|SE Platform www.iks-project.eu Copyright IKS Consortium
  23. 23. Page: 23Problem Statement Requirements Analysis & Engineering? Design Implementation & Test www.iks-project.eu Copyright IKS Consortium
  24. 24. Page: 24 Problem Statement Documents and Artifacts created in the software development process contain implicit information:  Type of the document (e.g. requirements specification)  Named Entities (e.g. actor „User“) Relations between the different document are not obvious  Thematically similar  Duplicates www.iks-project.eu Copyright IKS Consortium
  25. 25. Page: 25ID|SE Demo http://idse.cs.upb.de:8082/opencms/opencms/idse www.iks-project.eu Copyright IKS Consortium
  26. 26. Page: 26 ID|SE-Platform – Architecture<<OpenCMS>> ID|SE-Service-Platform IE/IR-Service-Orchestrators Content- Meta-Management- Data- System Search Evaluation- Services IE/IR-Services Content- Management Meta-Data-ModelDocument-Content- Meta-Data-Storage Storage www.iks-project.eu Copyright IKS Consortium
  27. 27. Page: 27Mapping with ReferenceArchitecture www.iks-project.eu Copyright IKS Consortium
  28. 28. Page: 28 ID|SE-Platform 1. Send Request to the ID|SE Platform <<OpenCMS>> WebserviceContent Management System ID|SE-Service Platform<<OpenCMS-Module>> GUI IEIR-ServiceOrchestrators DefaultMetaDataCreator Webservice IDefaultMetaDataCreator DefaultMetaDataCreator www.iks-project.eu Copyright IKS Consortium
  29. 29. Page: 29ID|SE-Platform2. Providing Documents ID|SE-Service Platform <<OpenCMS>> Content Management System IEIR-ServiceOrchestrators DefaultMetaData Creator <<component>> DocumentProvider Content-Management IProvideDocuments Webservice OpenCMSDocumentDocumentContent- Storage ProviderProxy Copyright IKS Consortium www.iks-project.eu
  30. 30. Page: 30ID|SE-Platform3. Generation of Meta-Data IE/IR-ServiceOrchestrators DefaultMetaDataCreator Evaluation IE/IR-Services Services Content- Pre- Named- Classi- Information- Extrac- pro- Clusterer Entity- fier Aggregator tion cessors Recognizer MetaDataModel www.iks-project.eu MetaDataStorage Copyright IKS Consortium
  31. 31. ID|SE-Platform Page: 314. Providing/Presenting Meta-Data Webservice <<OpenCMS>>Content Management Meta-Data-Search System<<OpenCMS-Module>> ArtifactSearchGUI IEIR-Services MetaDataSearchEngine Webservice MetaDataSearchEngine MetaDataModel www.iks-project.eu Copyright IKS Consortium MetaDataStorage
  32. 32. Page: 32 ID|SE Features Clustering of artefacts “Which artefacts are Classification about „XYZ‟ ” of artefacts Named No redundancy in entitysoftware specification recognition documents Duplicate Efficient way in Check browsing through content Facetted Search www.iks-project.eu Copyright IKS Consortium
  33. 33. Page: 33www.iks-project.eu Copyright IKS Consortium
  34. 34. Page: 34Evaluation CriteriaRecallPrecisionF-Measure www.iks-project.eu Copyright IKS Consortium
  35. 35. Page: 35 Evaluation of Semantic Features Entity Recognition Classification Clustering100% 100% 100%90% 88% 90% 90% 84% 80%80% 80% 77% 80% 74% 72%70% 70% 70% 64% 60% 58%60% 60% 56%50% 50% 50%40% 40% 40%30% 30% 30%20% 20% 20%10% 10% 10% 0% 0% 0% F-Measure Precision Recall F-Measure Precision Recall F-Measure Precision Recall www.iks-project.eu Copyright IKS Consortium
  36. 36. Page: 36 Lessons Learned ... Now you should know ...  ... the architectural requirements for a semantic CMS.  ... the integration concept of two loosely coupled columns.  ... the components of the reference architecture  ... how the reference architecture model can used to build a semantic CMS from scratch and how an extended system can be extended www.iks-project.eu Copyright IKS Consortium

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