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Towards Semantic Web Mining

Towards Semantic Web Mining. Bettina Berndt Andreas Hotho Gerd Stumme. Semantic Web Mining. Combination of Semantic Web and Web Mining Improve Web Mining using Semantic Web Improve Semantic Web using Web Mining. Overview. Web Mining Extracting Semantics from the Web

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Towards Semantic Web Mining

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  1. Towards Semantic Web Mining Bettina Berndt Andreas Hotho Gerd Stumme

  2. Semantic Web Mining • Combination of Semantic Web and Web Mining • Improve Web Mining using Semantic Web • Improve Semantic Web using Web Mining

  3. Overview • Web Mining • Extracting Semantics from the Web • Exploiting Semantics for Web Mining • Mining the Semantic Web • Closing the Loop • Conclusion/Assessment

  4. Web Mining • Discovers Local and Global Structure • Structured Data • Goals • Improvement of site design • Generate dynamic recommendations • Improve marketing • Main Areas • Web Content Mining • Web Structure Mining • Web Usage Mining

  5. Content Mining • Type of Text Mining • Uses Tags • Detect co-occurrences • Event detection • Reconstruction of page content • Relations in a domain

  6. Web Structure Mining • WebPages as a whole • Uses hyperlinks • Identify relevance • Single Pages • Five types of Web Pages • Head Pages • Navigation Pages • Content Pages • Look up Pages • Personal Pages

  7. Web Usage Mining • Request by Visitors • Additional Structure • Unintended Relationships

  8. Web Mining

  9. Disadvantages of Web Mining • Content/Structure • False positives • Unused • Human understandable • Large amount of data • Usage • Usage tracked by urls • General concepts • Multiplicity of events and urls

  10. cooperateswith(X,Y) • cooperateswith(Y,X) TOP NAME PERSON PERSON TITLE PROJECT COOPERATES COOPERATES -- -- WITH WITH Ontology WORKS-IN RESEARCHER RESEARCHER Semantic Web Mining Andreas Hotho WORKS-IN DAMLPROJ URI-SWMining - Relational Metadata URI-AHO WORKS-IN COOPERATES COOPERATES - - WITH WITH URI-GST WWW

  11. Outline • Web Mining • Extracting Semantics from the Web • Exploiting Semantics for Web Mining • Mining the Semantic Web • Closing the Loop • Conclusion/Assessment

  12. Extracting Semantics • Ontology Learning • Learn structures of Ontologies • Instance Learning • Populates the Ontologies

  13. Extracting Semantics • Ontology Learning • Semi-automatic approach • Merging • FCA-Merge • TITANIC • Instance Learning • Information Extraction

  14. Outline • Web Mining • Extracting Semantics from the Web • Exploiting Semantics for Web Mining • Mining the Semantic Web • Closing the Loop • Conclusion/Assessment

  15. How can the semantic web help with web mining ?

  16. Web Content/Structure Mining • Content Mining • Preprocess the input data • Apply heuristics • Creates a cluster • Web Structure Mining • Page Rank • Keyword Analysis • CLEVER

  17. Conceptual Clustering of Emails (and Bookmarks) using IE and Formal Concept Analysis for supporting navigation and retrieval.

  18. Web Usage Mining • Goal • Better understand user’s tendencies • Problem • Dynamic pages • How to take advantage of this? • Generate queries • Create usage paths • Classification scheme

  19. Advantages • Structured Model • Improve queries • Analyze single pages • Analyze ontologies • Users history

  20. Outline • Web Mining • Extracting Semantics from the Web • Exploiting Semantics for Web Mining • Mining the Semantic Web • Closing the Loop • Conclusion/Assessment

  21. How can web mining help build the semantic web?

  22. Semantic Web/Structure Mining • Intertwined • Relational Data Mining • Looks for patterns • Classification, regression, clustering and associations • Challenges • Scalability • Distributed

  23. Semantic Web Usage Mining • Goal • Requested page = ontology entity • Log files • Advantages • Understand search strategies • Improve navigation design • Personalize

  24. Outline • Web Mining • Extracting Semantics from the Web • Exploiting Semantics for Web Mining • Mining the Semantic Web • Closing the Loop • Conclusion/Assessment

  25. Mining to Learn Ontologies • Establish a concept hierarchy • OntEx • Determine Association rules • Discover combinations of concepts

  26. Mining to Learn Ontologies

  27. Filling the Ontologies

  28. Use Ontology to Mine

  29. Conclusion/Assesment • Semantic Structures in the Web can help Web mining • Web Mining can build the Semantic Web • Combine the two together • Different Idea • Combination of Products

  30. Questions?

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