Transcript F. Fakour
Beyond Basic Faceted Search Ben-Yitzhak, et al. Fahimeh Fakour CS 572 Summer 2010 Introduction 1. 2. 3. 4. 5. 6. 7. 8. 7/7/2010 Importance and significance Background Information Objective Related work Approach and Solutions Enhancements Contributions Pros & Cons Beyond Basic Faceted Search 2 1. Importance and Significance • Too much info • Transactions 7/7/2010 Beyond Basic Faceted Search 3 1. Importance and Significance (cont) • Categories, lists, and the human mind 7/7/2010 Beyond Basic Faceted Search 4 2. Background Information • 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 7/7/2010 Beyond Basic Faceted Search 5 3. Objective • Extend traditional facet – Beyond numbers Numbers Words • Search & Index correlated documents • Similarity to OLAP: multidimensional data 7/7/2010 Beyond Basic Faceted Search 6 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 7/7/2010 Beyond Basic Faceted Search 7 5. Approach & Solutions 5.1 5.2 5.3 5.4 5.5 5.6 7/7/2010 Technologies: Lucene & Solr Data Model Facet hierarchy: Forest Creating the facet paths Running the facet query Example Beyond Basic Faceted Search 8 5.1. Technologies: Lucene & Solr • Posting element: byte array of additional info (runtime accessible) docID, offset, payload • Matching document processing 7/7/2010 Beyond Basic Faceted Search 9 5.2. Data Model • Taxonomy: hierarchical relationships among facets – Predefined taxonomy – Acquired/Learned through documents • Facet-path forest – Tree: top-level facet 7/7/2010 Beyond Basic Faceted Search 10 5.3. Facet hierarchy: Forest Find facet hierarchies Map documents to that hierarchy 7/7/2010 Beyond Basic Faceted Search 11 5.4. Creating the facet paths • Posting element for document for each prefix of Pi • Add path to taxonomy index • Encode all k paths related to this document 7/7/2010 Beyond Basic Faceted Search 12 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 7/7/2010 Beyond Basic Faceted Search 13 5.6. Example Clothing Winter Coats Children’s Coats Color Red $30-$40 7/7/2010 $36-$40 All seasons Accessories Price $30-$35 Women’s Facet$clothing: Facet$clothing$children’s: Beyond Basic Faceted Search Blue doc1,doc2 doc1 14 6. Enhancements 7/7/2010 Beyond Basic Faceted Search 15 6.1. Business Intelligence • Qualitative rather than quantitative – Best sellers rather than number of books published by author 7/7/2010 Beyond Basic Faceted Search 16 6.2. Dynamic Facets: Welcome to the real world • Not always independent data • Example: – Running shorts • Different sizes per color • Location & price 7/7/2010 Beyond Basic Faceted Search 17 6.2. Dynamic Facets: Solution • Use tree over the data Manufacturer: Arthur’s Sports Model: Excalibur Type: Running Shorts Color: red 7/7/2010 Color: blue Color: black Size: small Size: medium Store: NY Store: SJ Price: $20 Price: $15 Beyond Basic Faceted Search Store: NY Price: $20 Store: SJ Price: $15 18 6.2. Dynamic Facets: Solution (cont) Manufacturer: Arthur’s Sports Model: Galahad Type: Running Shorts Store: SJ 7/7/2010 Color: blue Color: black, white Size: small Size: medium, large Price: $20 Price: $12 Beyond Basic Faceted Search 19 7. Contributions • “rich” aggregation : qualitative • Engineering details • Correlation in facet values 7/7/2010 Beyond Basic Faceted Search 20 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 7/7/2010 Beyond Basic Faceted Search 21 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? 7/7/2010 Beyond Basic Faceted Search 22 Thank You 7/7/2010 Beyond Basic Faceted Search 23 References 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/Hearfrom-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) 7/7/2010 Beyond Basic Faceted Search 24