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 1. Type or refine a search query 2. Navigate through multiple search query

4. INTRODUCTION Shortcoming 1. Should have richer insight into data 2. Too many independent facet hierarchies.

5. Related Work Multifaceted Search 1. Faceted Hierarchies 2. Mapping the documents OLAP- On Line Analytical Processing CUBE

6. Implementation of Basic Faceted Search Lucene Document Ingestion 1. Taxonomy before indexing 2. Taxonomy while indexing

7. Implementation of Basic Faceted Search

8. 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

11. Dynamic Facets

12. Correlated Facets

14. Shortcoming 1. Large index size 2. 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. 1. Flexible, Dynamic, Business intelligence aggregation 2. 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