1. Beyond Basic Faceted Search Ben-Yitzhak, et al. Fahimeh Fakour CS 572 Summer 2010

2. Introduction 1.Importance and significance 2.Background Information 3.Objective 4.Related work 5.Approach and Solutions 6.Enhancements 7.Contributions 8.Pros & Cons 7/7/20102Beyond Basic Faceted Search

3. 1. Importance and Significance Too much info Transactions 7/7/20103Beyond Basic Faceted Search

4. 1. Importance and Significance (cont) Categories, lists, and the human mind 7/7/20104Beyond Basic Faceted Search

5. 7/7/2010Beyond Basic Faceted Search5 Research done in IBM & Yahoo Research labs Facets, buckets, and categories – Navigate multiple paths for different ordering Free text queries List of matching documents with count 2. Background Information

6. 3. Objective Extend traditional facet – Beyond numbers NumbersWords Search & Index correlated documents Similarity to OLAP: multi- dimensional data 7/7/20106Beyond Basic Faceted Search

7. 4. Related Work Multifaceted search – Lexical subsumption – Synsets and hypernym – RawSugar social tagging Online Analytical Processing (OLAP) – Multi-dimensional data – Aggregation of data: Cube N-dimensional “group by” Exciting new technique 7/7/20107Beyond Basic Faceted Search

8. 5. Approach & Solutions 5.1Technologies: Lucene & Solr 5.2 Data Model 5.3Facet hierarchy: Forest 5.4Creating the facet paths 5.5Running the facet query 5.6Example 7/7/20108Beyond Basic Faceted Search

9. 5.1. Technologies: Lucene & Solr Posting element: docID, offset, payload Matching document processing byte array of additional info (runtime accessible) 7/7/20109Beyond Basic Faceted Search

10. 5.2. Data Model Taxonomy: hierarchical relationships among facets – Predefined taxonomy – Acquired/Learned through documents Facet-path forest – Tree: top-level facet 7/7/201010Beyond Basic Faceted Search

11. 5.3. Facet hierarchy: Forest Find facet hierarchies Map documents to that hierarchy 7/7/201011Beyond Basic Faceted Search

12. 5.4. Creating the facet paths Posting element for document for each prefix of P i Add path to taxonomy index Encode all k paths related to this document 7/7/201012Beyond Basic Faceted Search

13. 5.5. Running the facet query Terms: – Faceted query  string + taxonomy subtrees – Faceted result set  ranked list of documents matching query + counters Lucene: use the Taxonomy Index function to determine ordinal number of paths 7/7/201013Beyond Basic Faceted Search

14. 5.6. Example ClothingAll seasonsWomen’sAccessoriesChildren’sCoatsWinterCoats Price$30-$40$30-$35$36-$40 ColorRedBlue Facet$clothing: doc1,doc2 Facet$clothing$children’s:doc1 Facet$clothing: doc1,doc2 Facet$clothing$children’s:doc1 7/7/201014Beyond Basic Faceted Search

15. 6. Enhancements 7/7/201015Beyond Basic Faceted Search

16. 6.1. Business Intelligence Qualitative rather than quantitative – Best sellers rather than number of books published by author 7/7/201016Beyond Basic Faceted Search

17. 6.2. Dynamic Facets: Welcome to the real world Not always independent data Example: – Running shorts Different sizes per color Location & price 7/7/201017Beyond Basic Faceted Search

18. 6.2. Dynamic Facets: Solution Use tree over the data Manufacturer: Arthur’s Sports Model: Excalibur Type: Running Shorts Color: red Color: black Size: medium Store: SJ Price: $15 Store: NY Price: $20 Color: blue Size: small Store: SJ Price: $15 Store: NY Price: $20 7/7/201018Beyond Basic Faceted Search

19. 6.2. Dynamic Facets: Solution (cont) Manufacturer: Arthur’s Sports Model: Galahad Type: Running Shorts Store: SJ Color: black, white Size: medium, large Price: $12 Color: blue Size: small Price: $20 7/7/201019Beyond Basic Faceted Search

20. 7. Contributions “rich” aggregation : qualitative Engineering details Correlation in facet values 7/7/201020Beyond Basic Faceted Search

21. 8.1. Pros Detailed description of engineering aspects & design decisions Use of implemented technologies Clearly defines the scope of the paper Give foundation/background information Compatible with real life data 7/7/201021Beyond Basic Faceted Search

22. 8.2.  Cons  Experiments and testing: No qualitative measurement – effectiveness of “qualitative” facets Not explain relevance of some of the previous work Criteria for display/grouping? – Key use cases & known user access patterns not explained Build taxonomy: depth/breadth? 7/7/201022Beyond Basic Faceted Search

23. Thank You 7/7/201023Beyond Basic Faceted Search

24. References 247/7/201024Beyond Basic Faceted Search Ben-Yitzhak, et al. “Beyond Basic Faceted Search”. Proceedings of the international conference on Web search and web data mining. Pp.33-44, 2008. http://nadav.harel.org.il/papers/p33-ben-yitzhak.pdf “Faceted Search with Solr” Lucid Imagination. July 1, 2010. http://www.lucidimagination.com/Community/Hear- from-the-Experts/Articles/Faceted-Search-Solr “Faceted classification” Wikipedia. July 7, 2010 http://en.wikipedia.org/wiki/Faceted_classification Lemieux, Earley, and Associates. “Designing for Faceted Search” User Interface Engineering. July 6, 2010 http://www.uie.com/articles/faceted_search/ (Originally in KM World, March 2009) Mattman, Chris. “Query Models” (presentation slides for class)