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Beyond Basic Faceted Search

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This presentation, led by Chien-Ling Huang, explores advanced methodologies beyond basic faceted search. It delves into multifaceted and correlated facets to provide richer insights, benefiting business intelligence applications. Key sections include the introduction to faceted search concepts, implementation strategies using tools like Lucene, and solutions to common challenges such as large index sizes and aggregation complexities. The seminar culminates in a discussion of the pros and cons of dynamic facets and how they can transform data retrieval and analysis.

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Beyond Basic Faceted Search

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  1. Beyond Basic Faceted Search Presented by Chien-Ling Huang Jun. 30, 2011 Ori Ben-Yitzhak, Nadav Golbandi, Nadav Har’El, Ronny Lempel,Andreas Neumann, Shila Ofek-Koifman, Dafna Sheinwald, Eugene Shekita, Benjamin Sznajder, Sivan Yogev

  2. Overview • Introduction • Related Work • Implementation on Basic Facet Search • Extended multifaceted Search To Business Intelligence • Correlated Facets • Pros & Cons • Conclusion

  3. INTRODUCTION • What’s Faceted Search? • Typical user interaction with Faceted Search • Type or refine a search query • Navigate through multiple search query

  4. INTRODUCTION • Shortcoming • Should have richer insight into data • Too many independent facet hierarchies.

  5. Related Work • Multifaceted Search • Faceted Hierarchies • Mapping the documents • OLAP- On Line Analytical Processing CUBE

  6. Implementation of Basic Faceted Search • Lucene • Document Ingestion • Taxonomy before indexing • Taxonomy while indexing

  7. Implementation of Basic Faceted Search

  8. Implementation of Basic Faceted Search • Faceted query and Faceted result set FQ=(qc, TF) TF={tf1, tf2,….tfk} tfi=(Pi,ni) n>=1

  9. Extending Multifaceted Search to bussiness intelligence

  10. Extending Multifaceted Search to bussiness intelligence

  11. Extending Multifaceted Search to bussiness intelligence • Dynamic Facets

  12. Correlated Facets

  13. Correlated Facets

  14. Correlated Facets • Shortcoming • Large index size • Difficulty on aggregating counts

  15. Correlated Facets

  16. Pros and cons • Dynamic corpora • Less complexity • Allow multiple sub categories

  17. Conclusion • Extended the Basic Faceted Search. • Flexible, Dynamic, Business intelligence aggregation • Efficiently support correlated facets.

  18. Reference • Peter Anick and Suresh Tipirneni. Method and apparatus for automatic construction of faceted terminological feedback for document retrieval, 2003. US Patent 6519586. • Ramon Barquin and Herb Edelstein (editors). Building, Using and Managing the Data Warehouse. Prentice-Hall, Inc, 1997. • E.F. Codd, S.B. Codd, and C.T. Salley. Providingolap (on-line analytical processing) to user-analysts:An IT mandate. Technical Repor

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