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Data Frame Augmentation of Free Form Queries for Constraint Based Document Filtering

This study explores the augmentation of free-form queries for constraint-based document filtering, focusing on extracting numerical constraints from user queries. By utilizing a synergistic solution that combines keyword searches for speed and precision with semantic understanding for accuracy, the method enhances the effectiveness of search results. Detailed tests on various vehicle and recreational queries demonstrated significant improvements in precision while maintaining efficient performance across different data sets. This innovative approach can be applied broadly in search systems to improve query handling.

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Data Frame Augmentation of Free Form Queries for Constraint Based Document Filtering

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  1. Data Frame Augmentation of Free Form Queries for Constraint Based Document Filtering Andrew Zitzelberger

  2. Problem

  3. Constraint Based Queries

  4. Queries Test Queries     1) Find me a Wii game.     2) Find me a Honda for under 15 thousand dollars.     3) Roller Coaster more than 150 feet high     4) mountains at least 15K feet     5) games under $25     6) mountains less than 4 km     7) ps games < $40     8) coasters longer than 1000 feet     9) car for under 5 grand newer than 1990 with less than 115K miles    10) more than 15K miles under 5 grand newer than 2004

  5. Keywords + Semantics • Semantic queries are computationally expensive • Keyword queries are fast and simple • People are used to keyword queries • Synergistic solution: • extract numerical constraints from the query • use keywords to quickly narrow the search space • use constraints as a filter

  6. Data Frames Price     internal representation: Double     external representation: \$[1-9]\d{0,2}(,\d{3})*|...     ...     right units: (K)?\s*(cents|dollars|[Gg]rand|...)     canonicalization method: toUSDollars     comparison methods:         LessThan(p1: Price, p2: Price) returns (Boolean)         external representation: (less than|<|under|...)\s*{p2}|...         ...     end

  7. Data Frame Library

  8. Free Form Query • Car under 6 grand newer than 1990 with less than 115K miles

  9. Step 1: Condition Extraction • Car under 6 grand newer than 1990 with less than 115K miles • Extracted Conditions • (Price < 6000) • (Year > 1990) • (Distance  < 115000)

  10. Step 2: Remove Condition Values • Car under newer than with less than

  11. Step 3: Remove Stopwords • Car

  12. Step 4: Perform Keyword Search

  13. Step 5: Filter Document on Constraints • Keep page if every constraint is satisfied by at least one extracted value

  14. Experimental Setup • 300 web documents • 100 car+trucks pages from http://provo.craigslist.org • 100 video gaming pages from http://provo.craigslist.org • 50 mountain pages from http://en.wikipedia.org • 50 roller coaster pages from http://en.wikipedia.org • 10 queries • 8 with usable conditions • 2 data sets • test-development • blind test

  15. Precision@3/Query Type Keyword Queries Reduced Queries Data Frame Augmented Queries Dev-Test Queries 33% 40% 60% Blind-Test Queries 50% 46% 63% Overall 42% 43% 62% Results Summary • Precision increase for 56% of queries  • 75% for test-dev, 50% for blind-test • Precision never worse than keyword query • Most effective for short, focused documents

  16. Discussion • Issues: • inadequate narrowing or ranking of search space • noise caused by other numbers • Distance < 115000

  17. Future Work • Scalability • Indexing data frame extracted terms • Precision vs Recall trade-offs • Pay-as-you-go search construction

  18. Related Work • Question-Answering Systems • Keyword search over databases and semantic stores

  19. Questions?

  20. Query Keyword Condition Removed Keyword Data Frame Augmentation Find me a Wii game. 0.33 0.33 0.33 Find me a Honda for under 15 thousand dollars. 0.67 1.00 1.00 roller coaster more than 150ft high 0.33 0.33 0.67 mountains at least 15K ft 1.00 0.67 1.00 games under $25 0.00 0.33 0.67 mountains less than 4 km 0.00 0.00 0.33 ps games < 40 bucks 0.33 0.00 0.33 coasters longer than 1000 feet 0.33 1.00 1.00 car for under 6 grand newer than 1990 with less than 115K miles 0.33 0.33 0.67 more than 15K miles under 10 grand newer than 2000 0.00 0.00 0.00 Results (Test-Dev Set)

  21. Query Keyword Condition Removed Keyword Data Frame Augmentation Find me a Wii game. 0.67 0.67 0.67 Find me a Honda for under 15 thousand dollars. 0.67 1.00 1.00 roller coaster more than 150ft high 0.67 0.67 0.67 mountains at least 5K ft 0.33 0.33 0.67 games under $25 0.67 0.67 1.00 mountains less than 4 km 0.00 0.00 0.00 ps games < 40 bucks 0.33 0.33 0.33 coasters longer than 1000 feet 0.67 0.67 0.67 car for under 6 grand newer than 1990 with less than 115K miles 0.67 0.00 1.00 more than 15K miles under 10 grand newer than 2000 0.33 0.33 0.33 Results (Blind Test Set)

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